The Willingness and Affecting Factors Underlying Forest Farmers’ Socialization Method to Control Forest Biological Disasters
Abstract
1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Theoretical Base
2.3. Indicator Selection
2.4. Research Methods
3. Results
3.1. Sample Characteristics
3.2. Model Testing
3.3. Willingness to Hire SPC Companies
3.4. Willingness to Participate in Forest Insurance
3.5. Willingness to Become Forest Rangers
4. Discussion
5. Conclusions
- Regarding the willingness to engage SPC companies: An analysis, as presented in Table 2 and discussions, indicates that forest farmers with higher levels of education and a greater proportion of artificial forests are more inclined to hire SPC companies. This aligns with [52]’s findings. Forest farmers are generally willing to accept an average pest control cost of USD $108.73/ha, with those possessing higher education levels, previous village leadership experience, and personal preventive measures opting for approximately USD $65/ha as a more acceptable SPC cost.
- Concerning participation and willingness to pay premiums for forest insurance: Forest farmers exhibit diminished interest in purchasing forest insurance, consistent with prior research [27]. When organized by the village committee, forest farmers with higher education levels, advanced age, and previous village leadership roles tend to decrease their inclination to buy forest insurance. Conversely, those who have undertaken personal preventive measures advocate for reducing forest insurance premiums to approximately USD 5.5/ha, in line with the findings in [62]. However, among those willing to purchase forest insurance, premiums of up to around USD $6.5/ha may be acceptable.
- Regarding participation and expected income of forest farmers transitioning to forest rangers: Forest farmers express the highest willingness to assume roles as forest rangers, particularly in regions heavily reliant on forested land on the western side, a notable discovery. The village committee significantly influences the organization of forest rangers, with forest farmers having a greater share of artificial forests at home, showing a propensity to become rangers, consistent with the findings in [43]. An innovative observation is the substitution relationship detected between assuming village cadres and becoming forest rangers, particularly in areas with significant forest pest prevalence on the western side, which diminishes farmers’ inclination to become rangers. Moreover, village cadres on the western side advocate for higher incomes for forest rangers. Under the village committee’s organization, forest farmers with higher education levels, a greater proportion of artificial forests at home, and larger forest pest areas at home tend to lower their salary expectations and may accept an income of approximately USD $190/month.
6. Recommendations
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Bai, Y.; Wang, L.; Yuan, X. Pesticide control, physical control, or biological control? How to manage forest pests and diseases more effectively. Front. Ecol. Evol. 2023, 11, 1200268. [Google Scholar] [CrossRef]
- Canelles, Q.; Aquilue, N.; James, P.M.A.; Lawler, J.; Brotons, L. Global review on interactions between insect pests and other forest disturbances. Landsc. Ecol. 2021, 36, 945–972. [Google Scholar] [CrossRef]
- Cai, Q.; Cai, Y.; Wen, Y. Spatially Differentiated Trends between Forest Pest-Induced Losses and Measures for Their Control in China. Sustainability 2019, 11, 73. [Google Scholar] [CrossRef]
- Zheng, S.N.; Wei, W.; Zheng, S.F. A review of agricultural management organization and harmful organism risk management. Acta Ecol. Sin. 2019, 39, 460–473. [Google Scholar] [CrossRef]
- National People’s Congress. Forest Law of the People’s Republic of China (2019 Revision). 2019. Available online: http://www.forestry.gov.cn (accessed on 8 April 2025). (In Chinese)
- Jiang, Z.; Cai, Z.J.; Chen, S.L.; Qin, X. Study on the effect of “three rights separation” on farmers’ timber forest transfer behavior: Based on the theory of planned behavior. Jianghuai Forum 2018, 4, 14–20. [Google Scholar] [CrossRef]
- Ma, Z.; Clarke, M.; Church, S.P. Insights into individual and cooperative invasive plant management on family forestlands. Land Use Policy 2018, 75, 682–693. [Google Scholar] [CrossRef]
- Yang, Z.; Wang, X.; Zhang, Y. Recent advances in biological control of important native and invasive forest pests in China. Biol. Control 2014, 68, 117–128. [Google Scholar] [CrossRef]
- Department of Afforestation and Afforestation Management, State Forestry Administration (DAAM). Opinions of the General Office of the State Council on Further Strengthening the Prevention and Control of Forestry Pests; China Forestry Publishing House: Beijing, China, 2015. [Google Scholar]
- National Forestry and Grassland Administration Biodisaster Prevention and Control Center (NFGBPC). Forest Pest Monitoring and Forecasting 2022; China Forest Publishing House: Beijing, China, 2023. [Google Scholar]
- Cai, X.B. Analysis of socialized service and government responsibility for forest pest control. Low-Carbon World 2017, 19, 286–287. [Google Scholar] [CrossRef]
- Liu, J.; Liu, C.; Yang, H.Q.; Xu, S.L.; Bai, X.G.; Chen, J.J.; Zhang, H. The impact of forestland fragmentation on farmers’ investment incentives on forestland. Resour. Sci. 2018, 40, 2029–2038. [Google Scholar] [CrossRef]
- Graham, S.; Rogers, S. How Local Landholder Groups Collectively Manage Weeds in South-Eastern Australia. Environ. Manag. 2017, 60, 396–408. [Google Scholar] [CrossRef]
- Gong, Y.; Baylis, K.; Kozak, R.; Bull, G. Farmers’ risk preferences and pesticide use decisions: Evidence from field experiments in China. Agri. Econ. 2016, 47, 411–421. [Google Scholar] [CrossRef]
- Zhu, D.L. Farmers Are Growing Further and Further from the Land: Land Transfer and the Practice of Three Rights Separation in China. Soc. Sci. China 2021, 42, 24–43. [Google Scholar] [CrossRef]
- Guo, Q.; Fei, S.; Potter, K.M.; Liebhold, A.M.; Wen, J. Tree diversity regulates forest pest invasion. Proc. Natl. Acad. Sci. USA 2019, 116, 7382–7386. [Google Scholar] [CrossRef]
- Gao, G.F. Market supervision of socialized forest pest control. For. Dis. Insects China 2018, 37, 45–47. [Google Scholar] [CrossRef]
- Fan, L.; Niu, H.; Yang, X.; Qin, W.; Bento, C.P.; Ritsema, C.J.; Geissen, V. Factors affecting farmers’ behaviour in pesticide use: Insights from a field study in northern China. Sci. Total Environ. 2015, 537, 360–368. [Google Scholar] [CrossRef]
- Yang, B.; Cao, W.; Tian, C. Visual analysis of occurrence and control of forest pests with multi-view collaboration. J. Vis. 2019, 22, 177–195. [Google Scholar] [CrossRef]
- Ali, M.A.S.; Khan, S.U.; Khan, A.; Khan, A.A.; Zhao, M. Ranking of ecosystem services on the basis of willingness to pay: Monetary assessment of a subset of ecosystem services in the Heihe River basin. Sci. Total Environ. 2020, 734, 139447. [Google Scholar] [CrossRef]
- Stallman, H.R.; James, H.S. Determinants affecting farmers’ willingness to cooperate to control pests. Ecol. Econ. 2015, 117, 182–192. [Google Scholar] [CrossRef]
- Zhu, Y.L.; Qiu, X.H.; Wu, X.M.; He, D.B. Analysis of farmers’ intention of specialized pest control and its influencing factors based on Logit model: A case study of Zhenjiang City. J. Jiangxi Agr. Sci. 2015, 27, 121–124. [Google Scholar] [CrossRef]
- Liao, W.; Yuan, R.; Zhang, X.; Zhang, C.; Li, N. Influence of risk perception and policy support on the deviation of rural households’ demands and adoption behavior of the forestry socialized service. Front. Environ. Sci. 2023, 11, 1211310. [Google Scholar] [CrossRef]
- Wang, B.; Zhang, Z.T.; Ke, S.F.; Jiang, L.; Zhang, X. Analysis on cognition, satisfaction and demand willingness of foresters to forestry science and technology services: Based on a survey of 275 foresters in Yunnan Province. J. Beijing For. Univ. Soc. Sci. Ed. 2013, 12, 44–48. [Google Scholar] [CrossRef]
- Sheremet, O.; Healey, J.R.; Quine, C.P.; Hanley, N. Public Preferences and Willingness to Pay for Forest Disease Control in the UK. J. Agr. Econ. 2017, 68, 781–800. [Google Scholar] [CrossRef]
- Kong, F.B.; Ruan, H.; Liao, W.M. Influences of Forestry Socialized Service Supply on the Input-output Level of Farmers’ Land with Different Poverty Levels. Issue For. Econ. 2020, 40, 129–137. [Google Scholar] [CrossRef]
- Brunette, M.; Couture, S. Forest Insurance for Natural Events: An Overview by Economists. Forests 2023, 14, 289. [Google Scholar] [CrossRef]
- Qin, T.; Gu, X.; Tian, Z.; Pan, H.; Deng, J.; Wan, L. An empirical analysis of the factors influencing farmer demand for forest insurance: Based on surveys from Lin’an County in Zhejiang Province of China. J. For. Econ. 2016, 24, 37–51. [Google Scholar] [CrossRef]
- Feng, X.; Dai, Y. An innovative type of forest insurance in China based on the robust approach. For. Policy Econ. 2019, 104, 23–32. [Google Scholar] [CrossRef]
- Cipollaro, M.; Sacchelli, S. Demand and potential subsidy level for forest insurance market in Demand and potential subsidy level for forest insurance market in Italy. In Proceedings of the 2018 Seventh AIEAA Conference, Conegliano, Italy, 14–15 June 2018; Italian Association of Agricultural and Applied Economics (AIEAA): Parma, Italy, 2018. [Google Scholar]
- Zhao, H.C.; Wang, Z.Y. Research on determining forest pest insurance rate based on risk regionalization: A case study of Liaoning Province. For. Econ. 2015, 37, 29–33. [Google Scholar] [CrossRef]
- Haerullah, M.; Hardjanto, H.; Sunkar, A. The internal factors that affect the effectiveness of Forest Ranger Performance in Managing Forest Area of Gunung Gede Pangrango National Park. J. Nat. Resour. Environ. Manag. 2018, 8, 347–354. [Google Scholar] [CrossRef]
- Jia, T.Y.; Wang, Y.F.; Zhao, R. Implementation mechanism, effectiveness and dynamic adjustment of ecological forest ranger policy in China. World For. Res. 2023, 36, 1–7. [Google Scholar] [CrossRef]
- Zhu, H.G.; Zhang, Y.H.; Wan, S.W.; Liu, J.; Wang, X.; Liao, M.S. The Impact of Ecological Rangers’ Livelihood Capital Endowments on Their Livelihood Risks—Based on a Survey in Qianshan City, Anhui Province. For. Econ. 2022, 44, 71–84. Available online: http://www.cnki.com.cn/Article/CJFDTotal-LYJJ20220516001 (accessed on 16 April 2025).
- Han, Y.X.; Li, H.; Yang, Y.; Dong, L. Availability and influencing factors of socialized forestry services for farmers with different commercial forest management types: A survey of farmers in Zhejiang and Jiangxi provinces. For. Econ. 2019, 41, 79–88. [Google Scholar]
- Ali, M.A.S.; Zhang, Z.; Khan, S.U.; Khan, A.A.; Musa, M.; Rahman, P.; Hayat, Y. Does the location of the households’ matters? identifying the households’ willingness to pay and preference heterogeneity in advancement of vulnerable ecosystem services: An approach of choice experiment. Environ. Sci. Pollut. Res. Int. 2022, 30, 29859–29873. [Google Scholar] [CrossRef] [PubMed]
- Hu, Z.; Wang, Y.; Liu, Y.; Long, H.; Peng, J. Spatio-Temporal Patterns of Urban-Rural Development and Transformation in East of the “Hu Huanyong Line”, China. ISPRS Int. J. Geoinf. 2016, 5, 24. [Google Scholar] [CrossRef]
- Cai, Q.; Sun, B.; Zhang, X.; Bo, W.; Wang, G.; Zhou, Z. Forest Biological Disaster Control Behaviors of Forest Farmers and Their Spatial Heterogeneity in China. Forests 2024, 15, 970. [Google Scholar] [CrossRef]
- National Bureau of Statistics of China. Statistical Communiqué of the People’s Republic of China on the 2023 National Economic and Social Development. 2025. Available online: http://www.stats.gov.cn (accessed on 29 March 2025).
- Zhai, J.; Wang, L.; Liu, Y.; Wang, C.; Mao, X. Assessing the effects of China’s three-north shelter forest program over 40 years. Sci. Total Environ. 2023, 857, 159354. [Google Scholar] [CrossRef]
- Yan, J.; Sun, H.; Wang, Y.; Chen, Y.F.; Ma, H.T.; Yu, Z.J. Occurrence of major forestry pests in China in 2024 and trend prediction for 2025. Chin. For. Pest Manag. 2025, 1–5. [Google Scholar] [CrossRef]
- Zhang, Y.W.; Kant, S. Secure tenure or equal access? Farmers’ preferences for reallocating the property rights of collective farmland and forestland in Southeast China. Land Use Policy 2022, 112, 105814. [Google Scholar] [CrossRef]
- Marshall, G.R.; Coleman, M.J.; Sindel, B.M.; Reeve, I.J.; Berney, P.J. Collective action in invasive species control, and prospects for community-based governance: The case of serrated tussock (Nassella trichotoma) in New South Wales, Australia. Land Use Policy 2016, 56, 100–111. [Google Scholar] [CrossRef]
- Zhao, K.; Zhang, R.H.; Sun, P.F. The impact of capital endowment on farmers’ adoption of social agricultural services: A family life cycle perspective. Agr. Mod. Res. 2022, 1, 121–133. [Google Scholar] [CrossRef]
- Wang, J.B. Research on Economic Analysis of Biological Disasters in China’s Forestry and Its Control Countermeasures. Ph.D. Thesis, Chinese Academy of Forestry, Beijing, China, 2013. [Google Scholar]
- Bosshard, E.; Jansen, M.; Löfqvist, S.; Kettle, C.J. Rooting Forest Landscape Restoration in Consumer Markets—A Review of Existing Marketing-Based Funding Initiatives. Front. For. Glob. Change 2021, 3, 589982. [Google Scholar] [CrossRef]
- Liu, Y.; Xu, H.; Wang, X. Government subsidy, asymmetric information, and green innovation. Kybernetes Int. J. Syst. Cybern. 2022, 51, 3681–3703. [Google Scholar] [CrossRef]
- Guo, J.B. Research on Multi-Governance Mechanism of Cross-Domain Ecological Environment. Ph.D. Thesis, Jiangxi University, Nanchang, China, 2021. [Google Scholar]
- Houser, R.S. A Collaborative Model for Equitable Response and Recovery in Emergency Management. J. Emerg. Manag. Disaster Commun. 2022, 3, 57–81. [Google Scholar] [CrossRef]
- Zhong, K.B. National Emergency management system: Framework construction, evolution and improvement strategy. Reform 2020, 6, 5–18. [Google Scholar]
- Duguma, L.; Atela, J.; Minang, P.; Ayana, A.; Gizachew, B.; Nzyoka, J.; Bernard, F. Deforestation and Forest Degradation as an Environmental Behavior: Unpacking Realities Shaping Community Actions. Land 2019, 8, 26. [Google Scholar] [CrossRef]
- Clarke, M.; Ma, Z.; Snyder, S.; Floress, K. What are family forest owners thinking and doing about invasive plants? Landsc. Urban Plan 2019, 188, 80–92. [Google Scholar] [CrossRef]
- Yung, L.; Chandler, J.; Haverhals, M. Effective Weed Management, Collective Action, and Landownership Change in Western Montana. Invasive Plant Sci. Manag. 2015, 8, 193–202. [Google Scholar] [CrossRef]
- Niemiec, R.M.; Pech, R.; Norbury, G.L.; Byrom, A.E. Landowners’ Perspectives on Coordinated, Landscape-Level Invasive Species Control: The Role of Social and Ecological Context. Environ. Manag. 2017, 59, 477–489. [Google Scholar] [CrossRef]
- Khan, S.U.; Liu, G.; Zhao, M.; Chien, H.; Lu, Q.; Khan, A.A.; Misbahullah. Spatial prioritization of willingness to pay for ecosystem services. A novel notion of distance from origin’s impression. Environ. Sci. Pollut. Res. Int. 2020, 27, 3100–3112. [Google Scholar] [CrossRef]
- Duan, W.; Li, B.J.; Su, N.; Ma, L. Do nature reserves increase the risk of farmers’ livelihoods in surrounding communities?—Take 17 giant panda nature reserves in Sichuan and Shaanxi provinces as examples. For. Econ. 2021, 43, 58–70. [Google Scholar] [CrossRef]
- Chen, Q. Advanced Econometrics and Stata Applications; Higher Education Press: Beijing, China, 2010. [Google Scholar]
- Tanujaya, B.; Prahmana, R.C.I.; Mumu, J. Likert scale in social sciences research: Problems and difficulties. FWU J. Soc. Sci. 2022, 16, 89–101. [Google Scholar] [CrossRef]
- Cao, L.F.; Peng, C.; Wen, C.Y.; Zeng, Y.L. Forest insurance demand and differences of heterogeneous farmers in collective forest areas: Based on panel data of 500 farmers in Hunan Province. J. Agr. Tech. Econ. 2020, 5, 11. [Google Scholar]
- Wang, L.; Wang, E.; Mao, X.; Benjamin, W.; Liu, Y. Sustainable poverty alleviation through forests: Pathways and strategies. Sci. Total Environ. 2023, 904, 167336. [Google Scholar] [CrossRef] [PubMed]
- Chen, M.X.; Gong, Y.H.; Li, Y. Population Distribution and Urbanization on Both Sides of the Hu Huanyong Line: Answering the Premier’s Question. J. Geogr. Sci. 2016, 26, 1593–1610. [Google Scholar] [CrossRef]
- Qin, T.; Tian, Z.W.; Pan, H.X. Implementation effect, main problems and suggestions of China’s forest insurance premium subsidy policy. Econ. Asp. 2017, 1, 105–110. [Google Scholar] [CrossRef]
- Tanner, S.J.; Escobedo, F.J.; Soto, J.R. Recognizing the insurance value of resilience: Evidence from a forest restoration policy in the southeastern US. J. Environ. Manag. 2021, 289, 112442. [Google Scholar] [CrossRef]
- Poudel, A. Migration, youth workshops and forestry: Case studies from Nepal. Trees For. People 2021, 3, 100057. [Google Scholar] [CrossRef]
- Cai, Q.; Wang, G.Y.; Wen, X.Y.; Zhang, X.F.; Zhou, Z.F. Perceived Effectiveness and Responsibilities of the Forest Biological Disasters Control System of China: A Perspective of Government Administrators. Forests 2023, 14, 6. [Google Scholar] [CrossRef]
- Jiang, Y.; Long, H.; Tang, Y.T.; Deng, W.; Chen, K.; Zheng, Y. The impact of land consolidation on rural vitalization at village level: A case study of a Chinese village. J. Rural Stud. 2021, 86, 485–496. [Google Scholar] [CrossRef]
- Cao, Y.; Bai, Y.; Sun, M.; Xu, X.; Fu, C.; Zhang, L. Experience and lessons from the implementing of the latest Land Certificated Program in rural China. Land Use Policy 2022, 114, 105977. [Google Scholar] [CrossRef]
- Yang, J.; Wang, J.; Zhang, L.; Xiao, X.H. How to promote ethnic village residents’ behavior participating in tourism poverty alleviation: A tourism empowerment perspective. Front. Psychol. 2020, 11, 2064. [Google Scholar] [CrossRef]
- National Forestry and Grassland Administration; China Banking and Insurance Regulatory Commission. 2021 China Forest Insurance Development Report; China Forestry Publishing House: Beijing, China, 2022; Available online: https://news.cctv.com (accessed on 29 March 2025).
- Du, D. Research on the Impact of Forest Insurance Premium Subsidy on Forestry Output. Master’s Thesis, Guizhou University, Guiyang, China, 2024. [Google Scholar] [CrossRef]
- Liao, W.M.; Lin, J.; Shen, Y.Q.; Kong, F.B. Influence of socialized forestry services on the income gap of rural households. For. Sci. 2023, 59, 59–73. Available online: https://link.cnki.net/urlid/11.1908.S.20230309.1549.004 (accessed on 16 April 2025).
- Shen, X.X.; Duan, J.Y.; Zhu, S.Y. Analysis on social service model of agricultural green production. Agr. Resour. Reg. China 2020, 41, 15–20. Available online: https://link.cnki.net/urlid/11.3513.S.20190222.1455.002 (accessed on 16 April 2025).
- Liao, W.M.; Wang, L.; Gao, X.P. Can social services promote farmers’ input in forestry production factors?—Based on forestry pest control service survey. J. Huazhong Agr. Univ. Soc. Sci. Ed. 2022, 5, 101–113. [Google Scholar] [CrossRef]
- Sheremet, O.; Ruokamo, E.; Juutinen, A.; Svento, R.; Hanley, N. Incentivising Participation and Spatial Coordination in Payment for Ecosystem Service Schemes: Forest Disease Control Programs in Finland. Ecol. Econ. 2018, 152, 260–272. [Google Scholar] [CrossRef]
- Li, C.X.; Xu, J.B.; Wang, Y. Can Socialized Service of Agricultural Green Production Improve Agricultural Green Productivity? J. Agrotech. Econ. 2021, 9, 36–49. [Google Scholar] [CrossRef]
- Song, Y.; Peng, H.J. Review of the Research on Development Status, Restrictive Factors and Countermeasures of Forest Insurance Market. World For. Res. 2019, 32, 71–77. [Google Scholar] [CrossRef]
- Lei, X.; Chen, Z.C.; Huang, H.L. Empirical analysis of forest farmers’ willingness to pay for forest insurance: Based on the survey data of forest farmers in Fujian Province. Chin. For. Econ. 2020, 6, 107–110. [Google Scholar]
- Cai, Q.; Cai, Y.S.; Li, Y.; Hou, Y.L.; Wen, Y.L. Analysis on regional difference and influencing factors of forest pest control pressure. J. Nanjing For. Univ. Nat. Sci. Ed. 2019, 44, 111–118. [Google Scholar] [CrossRef]
Characteristics | Index | Description | Mean | Std. Err. | ||
---|---|---|---|---|---|---|
Total | East | West | ||||
Production decision makers | Age | Year | 51.933 | 53.044 | 50.654 | 12.299 |
Education | Year | 5.089 | 5.800 | 4.260 | 4.213 | |
Health Condition | very healthy = 5, healthy = 4, normal = 3, ill = 2, seriously ill = 1 | 3.882 | 4.100 | 3.632 | 1.179 | |
Village cadres | Yes = 1, No = 0 | 0.173 | 0.203 | 0.137 | 0.378 | |
Household forest management | Artificial forest proportion | Plantation area/total forest area | 0.491 | 0.385 | 0.613 | 0.812 |
FBD outbreak area | Hectare (ha.) | 0.682 | 0.996 | 0.323 | 3.232 | |
Control or not | Yes = 1, No = 0 | 0.440 | 0.478 | 0.396 | 0.497 | |
Organizing ability of village committee | SPC | very strong = 5, relatively strong = 4, general = 3, relatively weak = 2 and very weak = 1 | 4.031 | 4.142 | 3.914 | 0.988 |
Selecting forest rangers | 4.071 | 4.215 | 3.916 | 0.958 | ||
Forest insurance | 3.866 | 4.002 | 3.712 | 1.061 | ||
Willingness to participate | Hire a SPC company | very willing = 5, willing = 4, general = 3, reluctant = 2, very reluctant = 1 | 3.079 | 3.344 | 2.655 | 1.358 |
Purchase forest insurance | 2.545 | 2.722 | 2.319 | 1.170 | ||
Become a forest ranger | 3.485 | 2.972 | 4.084 | 1.512 | ||
Payment, compensation, and expected income | Pay for SPC company | USD/ha. | 108.730 | 119.393 | 27.692 | 747.841 |
Forest insurance premium | USD/year/ha. | 5.809 | 9.231 | 5.654 | 44.858 | |
Expected income of forest rangers | USD/month | 203.358 | 241.516 | 158.621 | 451.686 |
SUR | SEM | |||||
---|---|---|---|---|---|---|
HW | PW | HW | PW | |||
Coef. | Coef. | Coef. | Coef. | Coef. | Coef. | |
HW | −12.753 (8.864) | −25.319 (20.462) | ||||
Age | 0.006 (0.021) | −0.853 (0.781) | 0.008 (0.020) | −0.904 (0.802) | ||
Education | 0.172 ** (0.077) | −10.540 *** (2.959) | 0.196 *** (0.075) | −11.542 *** (3.174) | ||
Health condition | −0.220 (0.228) | 5.934 (8.672) | −0.222 (0.221) | 6.941 (8.988) | ||
Village cadres | −0.487 (0.551) | −34.683 * (20.961) | −0.312 (0.534) | −34.192 (21.751) | ||
Artificial forest proportion | 1.263 * (0.693) | 18.734 (26.568) | 1.077 (0.675) | 14.874 (28.318) | ||
FBD outbreak area | 0.081 (0.176) | −3.198 (6.659) | 0.086 (0.170) | −3.607 (6.850) | ||
Self-control | −0.429 (0.615) | −50.262 ** (23.368) | 0.200 (0.595) | −50.547 ** (24.172) | ||
Village committee organizing ability (VCOA) | −0.195 (0.303) | −11.396 (11.505) | −0.134 (0.293) | −11.108 (11.876) | ||
Constants | 3.227 (2.343) | 260.700 *** (88.973) | 141.982 *** (33.567) | 2.625 (2.263) | 266.913 (91.304) | 183.761 *** (69.996) |
Chi2 | 16.04 | 49.49 | 2.07 | 17.30 | 51.11 | 1.53 |
R2 | 0.276 ** | 0.575 *** | 0.019 | 0.247 ** | 0.587 *** | −0.034 |
SUR | SEM | |||||
---|---|---|---|---|---|---|
WPI | PP | WP | PP | |||
Coef. | Coef. | Coef. | Coef. | Coef. | Coef. | |
Willingness to Purchase | 0.371 ** (0.164) | 0.744 ** (0.374) | ||||
Age | −0.028 *** (0.006) | −0.013 * (0.008) | −0.028 *** (0.006) | −0.021 ** (0.011) | ||
Education | −0.089 *** (0.021) | −0.028 (0.027) | −0.083 *** (0.020) | −0.055 (0.036) | ||
Health condition | 0.035 (0.061) | 0.013 (0.070) | 0.033 (0.058) | 0.023 (0.071) | ||
Village cadres | −0.664 ** (0.327) | −0.292 (0.386) | −0.648 ** (0.312) | −0.490 (0.422) | ||
Artificial forest proportion | 0.464 (0.464) | 0.284 (0.536) | 0.478 (0.441) | 0.422 (0.546) | ||
FBD outbreak area | −0.053 (0.071) | 0.005 (0.082) | −0.043 (0.068) | −0.011 (0.084) | ||
Self-control | −0.076 (0.158) | −0.145 (0.181) | −0.109 (0.150) | −0.168 (0.181) | ||
VCOA | −0.422 *** (0.079) | −0.198 * (0.105) | −0.416 *** (0.077) | −0.324 ** (0.150) | ||
Constant | 5.735 *** (0.785) | 5.838 *** (1.027) | 3.498 *** (0.385) | 5.635 *** (0.762) | 6.920 *** (1.390) | 2.709 *** (0.811) |
Chi2 | 81.73 | 6.50 | 5.11 | 73.47 | 6.64 | 3.94 |
R2 | 0.625 *** | 0.114 | 0.018 ** | 0.622 *** | 0.135 | −0.039 ** |
Total | Eastern | Western | |||||||
---|---|---|---|---|---|---|---|---|---|
WB | EI | WB | EI | WB | EI | ||||
Coef. | Coef. | Coef. | Coef. | Coef. | Coef. | Coef. | Coef. | Coef. | |
WB | −23.966 *** (6.883) | 3.439 (10.721) | −0.047 (4.855) | ||||||
Age | −0.003 (0.011) | −0.058 (0.311) | −0.013 (0.014) | −0.059 (0.300) | −0.002 (0.008) | −0.097 (0.151) | |||
Education | 0.046 (0.037) | −2.349 ** (1.052) | −0.087 (0.057) | −1.685 (1.257) | −0.003 (0.023) | 0.538 (0.422) | |||
Health condition | −0.098 (0.121) | 3.223 (3.416) | 0.156 (0.225) | 0.183 (4.632) | −0.043 (0.066) | −0.686 (1.222) | |||
Village cadres | −0.755 ** (0.332) | 13.095 (10.053) | −0.938 ** (0.455) | −5.941 (11.382) | −0.029 (0.211) | 8.011 ** (3.884) | |||
Artificial forest proportion | 1.025 *** (0.314) | −27.802 *** (9.677) | −0.256 (0.482) | 5.070 (9.872) | 0.385 (0.768) | 6.042 (14.146) | |||
FBD outbreak area | 0.081 (0.120) | −2.891 ( 3.383) | 0.253 (0.159) | −1.237 (3.790) | −0.473 *** (0.081) | −4.665 *** (1.759) | |||
Self-control | −0.358 (0.325) | 12.110 (9.202) | −0.472 (0.514) | 2.491 (10.931) | 0.540 *** (0.181) | 1.951 (3.489) | |||
OAVC | 0.497 *** (0.147) | −12.259 *** (4.612) | 0.347 (0.225) | 1.453 (5.177) | 0.303 *** (0.082) | −6.809 *** (1.590) | |||
Constant | 1.558 (1.126) | 266.316 *** (32.831) | 289.130 *** (27.349) | 2.621 (1.611) | 235.558 *** (32.672) | 219.992 *** (34.017) | 3.435 *** (1.086) | 187.562 *** (20.123) | 157.213 *** (23.387) |
Chi2 | 40.90 | 22.46 | 12.12 | 17.04 | 6.25 | 0.10 | 40.90 | 22.46 | 0 |
R2 | 0.266 *** | 0.216 *** | 0.121 *** | 0.234 ** | 0.139 | −0.012 | 0.266 *** | 0.216 *** | 0 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Cai, Q.; Li, J.; Bo, W.; Han, F.; Hu, F.; Wang, J. The Willingness and Affecting Factors Underlying Forest Farmers’ Socialization Method to Control Forest Biological Disasters. Sustainability 2025, 17, 3850. https://doi.org/10.3390/su17093850
Cai Q, Li J, Bo W, Han F, Hu F, Wang J. The Willingness and Affecting Factors Underlying Forest Farmers’ Socialization Method to Control Forest Biological Disasters. Sustainability. 2025; 17(9):3850. https://doi.org/10.3390/su17093850
Chicago/Turabian StyleCai, Qi, Juewen Li, Wenjing Bo, Feng Han, Fangbing Hu, and Jiping Wang. 2025. "The Willingness and Affecting Factors Underlying Forest Farmers’ Socialization Method to Control Forest Biological Disasters" Sustainability 17, no. 9: 3850. https://doi.org/10.3390/su17093850
APA StyleCai, Q., Li, J., Bo, W., Han, F., Hu, F., & Wang, J. (2025). The Willingness and Affecting Factors Underlying Forest Farmers’ Socialization Method to Control Forest Biological Disasters. Sustainability, 17(9), 3850. https://doi.org/10.3390/su17093850