Do Not Be Anticlimactic: Farmers’ Behavior in the Sustainable Application of Green Agricultural Technology—A Perceived Value and Government Support Perspective
Abstract
:1. Introduction
2. Theoretical Basis and Mechanism Analysis
2.1. Theoretical Basis
2.2. Mechanism Analysis
2.2.1. Perceived Value and Sustainable Application of GAT
2.2.2. Government Support and Sustainable Application of GAT
2.2.3. Perceived Value and Government Support in the Sustainable Application of GAT
3. Data and Variables
3.1. Data Sources
3.2. Summary Statistics of Sample
3.3. Farmers’ Current Situation of Adopting GAT
3.4. Variables
3.4.1. Measuring Perceived Value
3.4.2. Measuring Government Support
3.4.3. Measuring Sustainable Application of GAT
3.4.4. Measuring Control Variables
3.5. Model Specification and Empirical Estimation Strategy
3.5.1. Basic Regression Analysis
3.5.2. Tests for Robustness and Endogeneity
4. Empirical Analysis
4.1. The Influence of Perceived Value on Farmers’ Sustainable Application of GAT
4.1.1. The Main Influence of Perceived Value on Farmers’ Sustainable Application of GAT
4.1.2. The Fractal Influence of Perceived Value on Farmers’ Sustainable Application of GAT
4.1.3. The Fractal Influence of Perceived Value Intensity on Farmers’ Sustainable Application of GAT
4.2. The Influence of Government Support on Farmers’ Sustainable Application of GAT
4.3. The Influence of Perceived Value and Government Support on Farmers’ Sustainable Application of GAT
4.3.1. Water-Saving Irrigation Technology
4.3.2. Green Pest Control Technology
4.3.3. Organic Fertilizer Substitution Technology
5. Endogeneity Test
6. Discussion
6.1. Conclusions
6.2. Policy Implications
6.3. Possible Contributions to Knowledge
6.4. Limitations and Areas for Further Research
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Variable Definition | Frequency | Percent | |
---|---|---|---|
Gender | Female | 636 | 55.89 |
Male | 502 | 44.11 | |
Age (year) | [20,35) | 222 | 19.50 |
[35,50) | 308 | 27.07 | |
[50,65) | 402 | 35.33 | |
65 and above | 206 | 18.10 | |
Years of schooling | [0,6) | 299 | 26.67 |
[6,9) | 542 | 47.63 | |
[9,12) | 231 | 20.29 | |
12 and above | 66 | 5.89 | |
Number of laborers | [1,2] | 634 | 55.71 |
[3,4] | 426 | 37.43 | |
5 and above | 78 | 6.85 | |
Farmland size (ha) | [0,5) | 411 | 36.12 |
[5,10) | 514 | 45.17 | |
[10,20) | 135 | 11.86 | |
20 and above | 78 | 6.85 | |
Income (wan CNY) | [0,3) | 182 | 15.99 |
[3,6) | 612 | 53.78 | |
[6,9) | 240 | 21.09 | |
9 and above | 104 | 9.14 | |
Joined an agricultural cooperative | Yes | 501 | 44.02 |
No | 637 | 55.98 |
Variable | Definition | Mean Value | Standard Deviation |
---|---|---|---|
Perceived value | Do you agree that sustainable application of GAT AGP has a positive significance | 0.701 | 0.411 |
Do you agree that sustainable application of GAT can bring benefits | 0.600 | 0.435 | |
Perceived monetary benefits | Do you agree that sustainable application of GAT can produce green products that can be sold at a better price | 0.653 | 0.476 |
Do you agree that sustainable application of GAT can make it easier to obtain financial subsidies | 0.461 | 0.332 | |
Perceived non-monetary benefits | Do you agree that sustainable application of GAT can improve the environment and reduce water, soil and other pollution | 0.501 | 0.500 |
Do you agree that sustainable application of GAT can win social recognition | 0.413 | 0.402 | |
Perceived monetary risks | Do you agree that sustainable application of GAT requires more monetary investment | 0.616 | 0.487 |
Do you agree that it may be more profitable to do something else rather than spend time and energy on sustainable application of GAT | 0.521 | 0.523 | |
Perceived non-monetary risks | Do you agree that sustainable application of GAT requires learning about the knowledge which is troublesome and unprofessional | 0.671 | 0.469 |
Do you agree that sustainable application of GAT may cause differences of opinion in the family and cause family problems | 0.417 | 0.399 | |
Intensity of perceived monetary benefits | Very strong = 5, strong = 4, indifferent = 3, weak = 2, very weak = 1 | 2.652 | 1.267 |
Intensity of perceived non-monetary benefits | 2.401 | 1.064 | |
Intensity of perceived monetary risks | 3.276 | 1.119 | |
Intensity of perceived non-monetary risks | 3.181 | 1.121 | |
Government support | Weighted mean of agricultural extension service and ecological subsidies | 0.406 | — |
Agricultural extension services | Do you receive the government agricultural extension service | 0.561 | 0.497 |
Ecological subsidies | Do you receive the government ecological subsidy | 0.250 | 0.433 |
Water-saving irrigation technology | Have you continued to use water-saving irrigation for more than two years | 0.139 | 0.347 |
Green pest control technology | Have you continued to use green pest control technology for more than two years | 0.609 | 0.488 |
Organic fertilizer substitution technology | Have you continued to use organic fertilizers substitution technology for more than two years | 0.210 | 0.407 |
Education | Year of schooling, year | 6.698 | 2.426 |
Health condition | Very good = 5, good = 4, indifferent = 3 bad = 2, very bad = 1 | 3.365 | 1.171 |
Labor | Number of laborers | 2.721 | 1.085 |
Income | Annual household income, wan CNY | 5.087 | 2.191 |
Farmland quality | Very good = 5, good = 4, indifferent = 3 bad = 2, very bad = 1 | 3.368 | 1.021 |
Farmland size | Actual value (ha) | 7.174 | 5.248 |
Traffic conditions | Very convenient = 5, convenient = 4, indifferent = 3, inconvenient = 2, very inconvenient = 1 | 3.376 | 1.199 |
Joined an agricultural cooperative | Yes = 1, no = 0 | 0.440 | 0.497 |
Variable | Model 1 (Probit) | Model 2 (OLS) | Model 3 (Probit) | Model 4 (OLS) | Model 5 (Probit) | Model 6 (OLS) |
---|---|---|---|---|---|---|
Water-Saving Irrigation Technology | Green Pest Control Technology | Organic Fertilizer Substitution Technology | ||||
Perceived value | 0.384 *** (0.028) | 0.062 *** (0.003) | 0.348 *** (0.021) | 0.092 *** (0.004) | 0.339 *** (0.022) | 0.080 *** (0.004) |
Education | 0.140 *** (0.030) | 0.023 *** (0.005) | 0.149 *** (0.024) | 0.038 *** (0.006) | 0.008 ** (0.025) | 0.004 (0.006) |
Health conditions | 0.341 *** (0.086) | 0.045 *** (0.011) | 0.141 ** (0.056) | 0.029 ** (0.014) | 0.149 ** (0.055) | 0.045 ** (0.014) |
Labor | 0.034 (0.064) | 0.001 (0.009) | 0.120** (0.051) | 0.028 ** (0.012) | 0.172 ** (0.050) | −0.049 *** (0.012) |
Income | 0.065 (0.047) | 0.002 (0.007) | 0.093** (0.034) | 0.028 ** (0.009) | 0.091** (0.034) | 0.025** (0.009) |
Farmland quality | −0.289 *** (0.073) | −0.038 *** (0.011) | −0.168** (0.058) | −0.048 ** (0.014) | −0.150 ** (0.060) | −0.035 ** (0.014) |
Traffic conditions | 0.012 (0.083) | 0.017 (0.011) | 0.024 (0.055) | 0.016 (0.014) | 0.189 *** (0.054) | 0.064 *** (0.014) |
Farmland size | −0.032 * (0.017) | −0.002 * (0.002) | −0.027 ** (0.013) | −0.007 ** (0.003) | −0.046 *** (0.012) | 0.013 *** (0.003) |
Joined an agricultural cooperative | 0.715 *** (0.171) | 0.104 *** (0.177) | 0.202 * (0.118) | 0.067** (0.030) | 0.261 ** (0.119) | 0.076 ** (0.030) |
Constant | 2.465 *** (0.315) | 0.031 (0.047) | 0.670** (0.252) | 0.625 *** (0.061) | 0.207 (0.255) | 0.563 *** (0.061) |
N | 1138 | 1138 | 1138 | 1138 | 1138 | 1138 |
Pseudo R2 | 0.414 | — | 0.382 | — | 0.327 | — |
−2 loglikelihood | 558.740 | — | 487.402 | — | 477.716 | — |
LR chi2 | 393.93 | — | 602.77 | — | 464.980 | — |
Prob>chi2 | 0.000 | — | 0.000 | — | 0.000 | — |
Variable | Model 1 (Probit) | Model 2 (OLS) | Model 3 (Probit) | Model 4 (OLS) | Model 5 (Probit) | Model 6 (OLS) |
---|---|---|---|---|---|---|
Water-Saving Irrigation Technology | Green Pest Control Technology | Organic Fertilizer Substitution Technology | ||||
Perceived monetary benefits | 0.159 (0.179) | 0.050 ** (0.021) | 0.353 ** (0.160) | 0.006 * (0.024) | 0.134 *** (0.205) | 0.687 *** (0.018) |
Perceived non-monetary benefits | 0.627 *** (0.136) | —0.079 *** (0.018) | 0.779 *** (0.116) | 0.137 *** (0.020) | 0.744 *** (0.145) | 0.094 *** (0.015) |
Perceived monetary risks | −1.404 *** (0.147) | −0.226 *** (0.019) | −1.329 *** (0.116) | −0.311 *** (0.022) | −1.869 *** (0.203) | −0.217 *** (0.017) |
Perceived non-monetary risks | −1.188 *** (0.128) | −0.213 *** (0.019) | −0.923 *** (0.108) | −0.217 *** (0.022) | −0.713 *** (0.162) | −0.078 *** (0.016) |
Constant | 0.953 ** (0.341) | 0.626 *** (0.050) | 0.138 (0.309) | 0.611 *** (0.057) | 0.283 (0.185) | 0.417 *** (0.043) |
Control Variables | YES | YES | YES | YES | YES | YES |
N | 1138 | 1138 | 1138 | 1138 | 1138 | 1138 |
Pseudo R2 | 0.431 | — | 0.394 | — | 0.733 | — |
−2 loglikelihood | 523.440 | — | 708.832 | — | 406.767 | — |
LR chi2 | 397.090 | — | 460.990 | — | 1115.46 | — |
Prob>chi2 | 0.000 | — | 0.000 | — | 0.000 | — |
Variable | Model 1 (Probit) | Model 2 (OLS) | Model 3 (Probit) | Model 4 (OLS) | Model 5 (Probit) | Model 6 (OLS) |
---|---|---|---|---|---|---|
Water−Saving Irrigation Technology | Green Pest Control Technology | Organic Fertilizer Substitution Technology | ||||
Perceived monetary benefits intensity | 0.150 *** (0.058) | 0.031 *** (0.007) | 0.169 *** (0.056) | 0.048 *** (0.007) | 0.126 *** (0.035) | 0.040 ** (0.012) |
Perceived non-monetary benefits intensity | 0.516 *** (0.074) | 0.083 *** (0.009) | 0.753 *** (0.078) | 0.125 *** (0.009) | 0.268 * (0.043) | 0.018 * (0.014) |
Perceived monetary risks intensity | −0.508 *** (0.064) | −0.079 *** (0.008) | −0.755 *** (0.072) | −0.116 *** (0.009) | −0.213 *** (0.039) | −0.066 *** (0.013) |
Perceived non-monetary risks intensity | −0.296 *** (0.061) | −0.046 *** (0.008) | −0.508 *** (0.066) | −0.077 *** (0.008) | −0.232 * (0.037) | −0.008 * (0.012) |
Constant | 0.468 (0.455) | 0.469 *** (0.063) | 1.102 ** (0.457) | 0.538 *** (0.065) | 1.844 *** (0.314) | 1.094 *** (0.101) |
Control Variables | YES | YES | YES | YES | YES | YES |
N | 1138 | 1138 | 1138 | 1138 | 1138 | 1138 |
Pseudo R2 | 0.478 | — | 0.120 | — | 0.139 | — |
−2 loglikelihood | 478.356 | — | 476.543 | — | 654.958 | — |
LR chi2 | 438.240 | — | 690.150 | — | 211.330 | — |
Prob>chi2 | 0.000 | — | 0.000 | — | 0.000 | — |
Variable | Model 1 (Probit) | Model 2 (OLS) | Model 3 (Probit) | Model 4 (OLS) | Model 5 (Probit) | Model 6 (OLS) |
---|---|---|---|---|---|---|
Water-saving irrigation Technology | Green Pest Control Technology | Organic Fertilizer Substitution Technology | ||||
Government support | 0.466 *** (0.110) | 0.174 * (0.113) | 0.397 *** (0.095) | 0.111 * (0.030) | 0.622 *** (0.101) | 0.175 * (0.026) |
Technical extension services | 0.174 * (0.113) | 0.136 * (0.022) | 0.356 *** (0.098) | 0.095 *** (0.027) | 0.617 *** (0.102) | 0.179 *** (0.030) |
Ecological subsidies | 0.594 *** (0.109) | 0.109 *** (0.020) | 0.574 *** (0.094) | 0.143 *** (0.023) | 0.776 *** (0.082) | 0.260 *** (0.026) |
Control variables | YES | YES | YES | YES | YES | YES |
Constant | 0.332 (0.229) | 0.353 *** (0.049) | 0.413* (0.214) | 0.359 *** (0.058) | 1.068 (0.211) | 0.831 *** (0.065) |
Control Variables | YES | YES | YES | YES | YES | YES |
N | 1138 | 1138 | 1138 | 1138 | 1138 | 1138 |
Pseudo R2 | 0.157 | — | 0.116 | — | 0.178 | — |
−2 loglikelihood | 776.313 | — | 1034.078 | — | 1251.327 | — |
LR chi2 | 144.220 | — | 135.740 | — | 270.900 | — |
Prob>chi2 | 0.000 | — | 0.000 | — | 0.000 | — |
Variable | Water-Saving Irrigation Technology | |||
---|---|---|---|---|
(1) | (2) | (3) | (4) | |
Perceived monetary benefits × Ecological subsidies | 0.153 * (0.121) | — | — | — |
Perceived monetary risks × Ecological subsidies | — | −0.631 *** (0.191) | — | — |
Perceived non-monetary benefits × Technical extension services | — | — | 0.840 *** (0.103) | — |
Perceived non-monetary risks × Technical extension services | — | — | — | −0.580 *** (0.118) |
Control variables | YES | YES | YES | YES |
N | 1138 | 1138 | 1138 | 1138 |
Pseudo R2 | 0.121 | 0.133 | 0.176 | 0.148 |
−2 loglikelihood | 809.128 | 797.786 | 758.473 | 784.515 |
LR chi2 | 111.410 | 122.750 | 162.060 | 136.020 |
Prob>chi2 | 0.000 | 0.000 | 0.000 | 0.000 |
Variable | Green Pest Control Technology | |||
---|---|---|---|---|
(1) | (2) | (3) | (4) | |
Perceived monetary benefits × Ecological subsidies | 0.440 *** (0.104) | — | — | — |
Perceived monetary risks × Ecological subsidies | — | −0.517 *** (0.150) | — | — |
Perceived non-monetary benefits × Technical extension services | — | — | 0.846 *** (0.916) | — |
Perceived non-monetary risks × Technical extension services | — | — | — | −0.331*** (0.095) |
Control variables | YES | YES | YES | YES |
N | 1138 | 1138 | 1138 | 1138 |
Pseudo R2 | 0.086 | 0.082 | 0.145 | 0.082 |
−2 loglikelihood | 1062.966 | 1073.717 | 1000.235 | 1074.451 |
LR chi2 | 100.820 | 96.100 | 169.58 | 95.37 |
Prob>chi2 | 0.000 | 0.000 | 0.000 | 0.000 |
Variable | Organic Fertilizer Substitution Technology | |||
---|---|---|---|---|
(1) | (2) | (3) | (4) | |
Perceived monetary benefits × Ecological subsidies | 0.516 *** (0.154) | — | — | — |
Perceived monetary risks × Ecological subsidies | — | −0.075 * (0.117) | — | — |
Perceived non-monetary benefits × Technical extension services | — | — | 0.617 *** (0.095) | — |
Perceived non-monetary risks × Technical extension services | — | — | — | −0.160 * (0.083) |
Control variables | YES | YES | YES | YES |
N | 1138 | 1138 | 1138 | 1138 |
Pseudo R2 | 0.184 | 0.093 | 0.159 | 0.095 |
−2 loglikelihood | 1242.492 | 1080.448 | 1080.331 | 1177.099 |
LR chi2 | 279.740 | 141.780 | 241.900 | 145.130 |
Prob>chi2 | 0.000 | 0.000 | 0.000 | 0.000 |
Variable | 2SLS | Probit | OLS | ||
---|---|---|---|---|---|
Technical Extension Services | Ecological Subsidies | Sustainable Application of GAT | Sustainable Application of GAT | Sustainable Application of GAT | |
Owning a smartphone | 0.316 *** (0.154) | 0.075 * (0.111) | 0.255 *** (0.117) | 0.256 *** (0.190) | 0.302 *** (0.098) |
Technical extension services | — | — | — | 0.156 ** (0.110) | 0.201 * (0.030) |
Ecological Subsidies | — | — | — | 0.496 *** (0.198) | 0.633 *** (0.053) |
N | 1138 | ||||
F | 16.510 | 17.680 | 17.253 | 17.101 | 16.486 |
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Xiang, W.; Gao, J. Do Not Be Anticlimactic: Farmers’ Behavior in the Sustainable Application of Green Agricultural Technology—A Perceived Value and Government Support Perspective. Agriculture 2023, 13, 247. https://doi.org/10.3390/agriculture13020247
Xiang W, Gao J. Do Not Be Anticlimactic: Farmers’ Behavior in the Sustainable Application of Green Agricultural Technology—A Perceived Value and Government Support Perspective. Agriculture. 2023; 13(2):247. https://doi.org/10.3390/agriculture13020247
Chicago/Turabian StyleXiang, Wen, and Jianzhong Gao. 2023. "Do Not Be Anticlimactic: Farmers’ Behavior in the Sustainable Application of Green Agricultural Technology—A Perceived Value and Government Support Perspective" Agriculture 13, no. 2: 247. https://doi.org/10.3390/agriculture13020247
APA StyleXiang, W., & Gao, J. (2023). Do Not Be Anticlimactic: Farmers’ Behavior in the Sustainable Application of Green Agricultural Technology—A Perceived Value and Government Support Perspective. Agriculture, 13(2), 247. https://doi.org/10.3390/agriculture13020247