Knowledge and Farmers’ Adoption of Green Production Technologies: An Empirical Study on IPM Adoption Intention in Major Indica-Rice-Producing Areas in the Anhui Province of China
Abstract
:1. Introduction
2. Conceptual Framework
3. Materials and Methods
3.1. Data and Research Design
3.1.1. Description of the Study Region
3.1.2. Survey Design and Data Collection
3.2. Methods
3.2.1. Theoretical Model
3.2.2. Empirical Model and Variable Descriptions
3.2.3. Estimation Method
4. Results
4.1. Descriptive Statistics
4.1.1. Summary Statistics of Respondents
4.1.2. Agricultural Production Knowledge and Farmers’ Willingness to Adopt IPM Technology
4.1.3. Other Factors and Farmers’ Willingness to Adopt IPM Technology
4.2. Regression Results
4.2.1. Comprehensive Agricultural Production Knowledge and Farmers’ IPM Adoption Intention
4.2.2. Disciplinary Knowledge and Farmers’ IPM Adoption Intention
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Comprehensive Test | Knowledge Disciplines | ||||
---|---|---|---|---|---|
Pest Management | Nutrient Management | Agro-Environment | Cultivation Technology | ||
Full Score | 400 | 100 | 100 | 100 | 100 |
Score | 161 | 40 | 44 | 22 | 56 |
Variable Name | Definitions | Mean | Std Dev. |
---|---|---|---|
Explanatory variable | |||
Wi | The ith farmer’s willingness to adopt IPM technology 1 = Yes, 0 = No | 0.49 | 0.50 |
Key explanatory variables | |||
Scorei0 | score of comprehensive test | 160.87 | 44.94 |
Scorei1 | score of the pest management discipline | 39.52 | 10.95 |
Scorei2 | score of the nutrient management discipline | 43.78 | 22.55 |
Scorei3 | score of the agro-environment discipline | 21.84 | 20.37 |
Scorei4 | score of the cultivation technology discipline | 55.73 | 13.75 |
Individual variables | |||
Gender | 1 = Female, 0 = Male | 0.44 | 0.50 |
Age | year | 54.23 | 10.53 |
Education | education years | 4.26 | 3.94 |
Training | agrotechnical training experience 1 = Yes, 0 = No | 0.46 | 0.50 |
Family variables | |||
NA employment | Non-agricultural employment ratio (%) | 26.81 | 33.35 |
Land | Per capita arable land area (acre) | 0.13 | 0.11 |
Income | Average family income (¥1000) | 36.20 | 42.27 |
Characteristics | Min | Max | Category | Sample Size | Percentage (%) |
---|---|---|---|---|---|
Age | 28 | 79 | (20,30] | 1 | 0.10 |
(30,40] | 69 | 7.03 | |||
(40,50] | 326 | 33.23 | |||
(50,60] | 247 | 25.18 | |||
(60,80] | 338 | 34.45 | |||
Education Years | 0 | 16 | [0,6) | 419 | 42.71 |
[6,9) | 325 | 33.13 | |||
[9,12) | 207 | 21.10 | |||
[12,16) | 28 | 2.85 | |||
[16,19) | 2 | 0.20 | |||
Training | 0 | 1 | 0 | 525 | 53.52 |
1 | 456 | 46.48 | |||
NA employment | 0 | 100 | 0 | 544 | 55.45 |
(0,20] | 32 | 3.26 | |||
(20,40] | 75 | 7.65 | |||
(40,60] | 111 | 11.31 | |||
(60,80] | 165 | 16.82 | |||
(80,100] | 54 | 5.50 | |||
Land Size | 0.01 | 2.30 | (0,0.3] | 942 | 96.02 |
(0.3,0.6] | 33 | 3.36 | |||
(0.6,0.9] | 5 | 0.51 | |||
(0.9,2.3] | 1 | 0.10 |
Sample Size | Willing to Adopt IPM (%) | |
---|---|---|
Integrated score | ||
(0,140] | 349 | 42 |
(140,180] | 337 | 46 |
>180 | 295 | 59 |
Score of pest management discipline | ||
(0,35] | 325 | 49 |
(35,45] | 377 | 54 |
>45 | 279 | 57 |
Score of nutrient management discipline | ||
(0,50] | 501 | 46 |
>50 | 480 | 51 |
Score of agro-environment discipline | ||
(0,25) | 343 | 44 |
[25,50] | 604 | 57 |
>50 | 34 | 76 |
Score of cultivation technology discipline | ||
(0,50] | 507 | 49 |
(50,75] | 312 | 45 |
>75 | 162 | 54 |
Sample Size | Willing to Adopt IPM (%) | |
---|---|---|
Gender | ||
Female | 428 | 42 |
Male | 553 | 54 |
Age | ||
≤45 | 248 | 57 |
(45,55] | 253 | 56 |
(55,60] | 192 | 47 |
>60 | 288 | 36 |
Education years | ||
0 | 419 | 40 |
(0,6] | 325 | 51 |
>6 | 237 | 60 |
Agrotechnical training experience | ||
Yes | 456 | 54 |
No | 525 | 44 |
Non-agricultural employment ratio in the family (%) | ||
[0,35] | 196 | 30 |
(35,50] | 203 | 48 |
(50,75] | 327 | 48 |
>75 | 255 | 64 |
Per capita arable land area of the family (acre) | ||
(0,0.08] | 301 | 44 |
(0.08,0.14] | 357 | 48 |
>0.14 | 323 | 54 |
Average family income (¥1000) | ||
(0,16] | 328 | 44 |
(16,46] | 391 | 47 |
>46 | 262 | 57 |
Variables | Model ① | Model ② | Model ③ | Model ④ |
---|---|---|---|---|
Key explanatory variables | ||||
Scorei0 | 0.004 ** (0.002) [0.001] ** | 0.001 ** (0.000) | 0.004 ** (0.002) [0.001] ** | 0.001 ** (0.000) |
Individual variables | ||||
Gender | −0.479 *** (0.160) [−0.108] *** | −0.110 *** (0.036) | −0.305 * (0.165) [−0.065] | −0.066 * (0.036) |
Age | −0.018 ** (0.008) [−0.004] ** | −0.004 ** (0.002) | −0.007 (0.008) [−0.002] | −0.002 (0.002) |
Education | 0.025 (0.020) [0.006] | 0.006 (0.005) | 0.023 (0.021) [0.005] | 0.005 (0.005) |
Training | 0.323 ** (0.137) [0.073] ** | 0.072 ** (0.031) | 0.379 *** (0.145) [0.081] *** | 0.081 ** (0.031) |
Family variables | ||||
NA employment | 0.014 *** (0.003) [0.003] *** | 0.003 *** (0.001) | 0.009 *** (0.003) [0.002] *** | 0.002 *** (0.001) |
Land | 0.398 (0.683) [0.089] | 0.094 (0.154) | 0.001 (0.525) [0.000] | 0.002 (0.112) |
Income | 0.001 (0.002) [0.000] | 0.000 (0.000) | −0.001 (0.002) [−0.000] | −0.000 (0.000) |
Regional dummies | Controlled | Controlled | ||
Intercept | −0.705 (0.644) | 0.343 ** (0.145) | −1.363 ** (0.678) | 0.196 (0.145) |
Sample size | 981 |
Variables | Model ⑤ | Model ⑥ | Model ⑦ | Model ⑧ |
---|---|---|---|---|
Key explanatory variables | ||||
Pest-management knowledge | 0.027 *** (0.007) [0.006] *** | 0.006 *** (0.002) | 0.026 *** (0.008) [0.006] *** | 0.006 *** (0.002) |
Nutrient-management knowledge | 0.000 (0.004) [0.000] | 0.000 (0.001) | 0.003 (0.004) [0.001] | 0.001 (0.001) |
Agro-environment knowledge | −0.001 (0.004) [0.000] | −0.000 (0.001) | −0.003 (0.004) [−0.001] | −0.001 (0.001) |
Cultivation-technology knowledge | 0.001 (0.005) [0.000] | 0.000 (0.001) | −0.000 (0.005) [−0.000] | −0.000 (0.001) |
Individual variables | ||||
Gender | −0.487 *** (0.161) [−0.108] *** | −0.111 *** (0.036) | −0.311 * (0.165) [−0.066] * | −0.067 * (0.036) |
Age | −0.017 ** (0.008) [−0.004] ** | −0.004 ** (0.002) | −0.007 (0.008) [−0.001] | −0.001 (0.002) |
Education | 0.024 (0.021) [0.005] | 0.005 (0.005) | 0.020 (0.021) [0.004] | 0.004 (0.005) |
Training | 0.262 (0.139) [0.058] | 0.058 * (0.031) | 0.329 ** (0.148) [0.069] ** | 0.070 ** (0.032) |
Family variables | ||||
NA employment | 0.014 *** (0.003) [0.003] *** | 0.003 *** (0.001) | 0.008 *** (0.003) [0.002] *** | 0.002 *** (0.001) |
Land | 0.354 (0.641) [0.079] | 0.084 (0.147) | −0. 042 (0.524) [−0.009] | −0.006 (0.105) |
Income | 0.001 (0.002) [0.000] | 0.000 (0.000) | −0.001 (0.002) [−0.000] | −0.000 (0.000) |
Regional dummies | Controlled | Controlled | ||
Intercept | −1.187 * (0.684) | 0.239 (0.151) | −1.671 ** (0.710) | 0.134 (0.149) |
Sample size | 981 |
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Sun, X.; Lyu, J.; Ge, C. Knowledge and Farmers’ Adoption of Green Production Technologies: An Empirical Study on IPM Adoption Intention in Major Indica-Rice-Producing Areas in the Anhui Province of China. Int. J. Environ. Res. Public Health 2022, 19, 14292. https://doi.org/10.3390/ijerph192114292
Sun X, Lyu J, Ge C. Knowledge and Farmers’ Adoption of Green Production Technologies: An Empirical Study on IPM Adoption Intention in Major Indica-Rice-Producing Areas in the Anhui Province of China. International Journal of Environmental Research and Public Health. 2022; 19(21):14292. https://doi.org/10.3390/ijerph192114292
Chicago/Turabian StyleSun, Xiaolong, Jing Lyu, and Candi Ge. 2022. "Knowledge and Farmers’ Adoption of Green Production Technologies: An Empirical Study on IPM Adoption Intention in Major Indica-Rice-Producing Areas in the Anhui Province of China" International Journal of Environmental Research and Public Health 19, no. 21: 14292. https://doi.org/10.3390/ijerph192114292