Study on the Effect of Digital Technology Adoption and Farmers’ Cognition on Fertilizer Reduction and Efficiency Improvement Behavior
Abstract
:1. Introduction
2. Theoretical Framework and Hypothesis
2.1. Impact Mechanism of Digital Technology Adoption (DTA) on Farmer’s Choices of Fertilizer-Reduction and Efficiency-Improving Technologies (FETs)
2.2. Impact Mechanism of Farmers’ Cognition (FC) on their Choices of FETs
2.3. Analysis of the Mediating Effect of Farmers’ Cognition (FC)
3. Data and Methods
3.1. Data Source
3.2. Data Processing
3.3. Variables Design
3.4. Research Methods
4. Results and Analysis
4.1. Main Observations
4.2. Mediating Effect Examination
4.3. Robustness Tests
4.3.1. Replacement of Mediating Effect Test
4.3.2. Counterfactual Estimation of Propensity Score Matching
4.4. Endogenous Tests
4.5. Further Discussion
4.5.1. Heterogeneity Analysis Based on Educational Level
4.5.2. Heterogeneity Analysis Based on Planting Scale
5. Conclusions and Implications
Author Contributions
Funding
Institutional Review Board Statement
Data Availability Statement
Conflicts of Interest
References
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DTA/FETs | Sample | Relative Frequency | |
---|---|---|---|
Are you able to use the Internet to obtain agricultural information? | I can use the Internet to obtain information related to agriculture | 436 | 35.86% |
How is your family’s adoption of fertilizer reduction and efficiency-enhancing technology? | Not adopted | 455 | 37.42% |
Adopt only 1 type | 528 | 43.42% | |
Adopt 2 or more types | 233 | 19.17% |
Category | Definition | Mean | Std. Dev. | Factor Analysis Result | |||
---|---|---|---|---|---|---|---|
Factor1 | Factor2 | Factor3 | Factor4 | ||||
Ecology cognition | I am very familiar with the national ecological restoration policy. 1 = Strongly disagree; 2 = Disagree; 3 = General; 4 = Familiar; 5 = Very familiar | 2.370 | 1.174 | 0.784 | 0.148 | 0.141 | 0.068 |
I can identify environmental issues in the surrounding ecosystem. 1 = Strongly disagree; 2 = Disagree; 3 = General; 4 = Consistent; 5 = Very Consistent | 2.310 | 1.231 | 0.855 | 0.098 | 0.095 | 0.032 | |
I have mastered the relevant technologies to deal with ecological and environmental issues. 1 = Not at all; 2 = Not mastered; 3 = General; 4 = Mastered; 5 = Fully mastered | 1.640 | 0.952 | 0.748 | 0.200 | 0.178 | 0.029 | |
Market cognition | I can grasp the trends of the apple market. 1 = Strongly disagree; 2 = Disagree; 3 = General; 4 = Consistent; 5 = Very consistent | 2.410 | 1.211 | 0.156 | 0.843 | 0.035 | 0.106 |
I think the price fluctuations in the apple market are relatively stable. 1 = Strongly disagree; 2 = Disagree; 3 = General; 4 = Consistent; 5 = Very consistent | 2.500 | 1.257 | 0.181 | 0.864 | 0.180 | −0.001 | |
I can grasp the timing of Apple’s sales 1 = Strongly disagree; 2 = Disagree; 3 = General; 4 = Consistent; 5 = Very consistent | 2.790 | 1.242 | 0.148 | 0.699 | 0.402 | 0.003 | |
Risk cognition | I can control the production cost of green production. 1 = Strongly disagree; 2 = Disagree; 3 = General; 4 = Consistent; 5 = Very consistent | 2.720 | 1.306 | 0.043 | 0.267 | 0.764 | −0.021 |
I can control the quality of green production fruits. 1 = Strongly disagree; 2 = Disagree; 3 = General; 4 = Consistent; 5 = Very consistent | 3.150 | 1.279 | 0.150 | 0.126 | 0.762 | 0.134 | |
When facing a decline in the price of regular apples, I believe that adopting green production can reduce risks. 1 = Strongly disagree; 2 = Disagree; 3 = Neutral; 4 = Agree; 5 = Strongly agree | 2.879 | 0.655 | 0.287 | 0.052 | 0.625 | 0.238 | |
Technology cognition | I understand green production technologies. 1 = Very unfamiliar; 2 = Unfamiliar; 3 = General; 4 = Familiar; 5 = Very familiar | 3.840 | 1.109 | 0.057 | 0.002 | 0.086 | 0.896 |
I believe that implementing green production for apples will improve efficiency. 1 = Strongly disagree; 2 = Disagree; 3 = Neutral; 4 = Agree; 5 = Strongly agree | 3.490 | 1.305 | −0.005 | 0.052 | 0.123 | 0.708 | |
In order to attract consumers and wholesalers, I am willing to adopt new technologies to improve the quality of fruits. 1 = Strongly unwilling; 2 = Unwilling; 3 = Neutral; 4 = Willing; 5 = Strongly willing | 3.800 | 1.158 | 0.088 | 0.045 | 0.053 | 0.920 |
Variable Category | Definition | Mean | Std. Dev. | |
---|---|---|---|---|
Explained variable | FETs | Do you use soil testing and formulated fertilization? Yes = 1; No = 0 | 0.121 | 0.326 |
Do you use water-fertilizer integration technology? Yes = 1; No = 0 | 0.571 | 0.495 | ||
Do you use slow/controlled fertilization? Yes = 1; No = 0 | 0.162 | 0.369 | ||
Core explanatory variable | DTA | Is it possible to access agricultural information through the Internet? Yes = 1; No = 0 | 0.359 | 0.481 |
Mediating variable | FC | Comprehensive score after factor analysis of each dimension of FC | 0.386 | 0.318 |
Common factor 1 score for ecological cognition | 0 | 1 | ||
Common factor 2 score for market cognition | 0 | 1 | ||
Common factor 3 score for risk cognition | 0 | 1 | ||
Common factor 4 score for technical cognition | 0 | 1 | ||
Control variables | Individual characteristics | Gender: Male = 1; Female = 0 | 0.728 | 0.444 |
Age: Age of the head of household | 54.663 | 9.690 | ||
Educational level: Number of years of education received by the household head | 7.294 | 3.390 | ||
Family characteristics | Orchard area: Apple planting area | 15.155 | 52.119 | |
Non-agricultural employment: Do any family members have non-agricultural employment? Yes = 1; No = 0 | 0.590 | 0.492 | ||
Environmental characteristics | Degree of orchard fragmentation: Number of orchard plots owned | 3.989 | 3.218 | |
Level of government green production promotion: Is there relevant training? Yes = 1; No = 0 | 0.750 | 0.435 |
Variables | Multivariateprobit1 | Multivariateprobit2 | OLS3 | ||||
---|---|---|---|---|---|---|---|
STFF | WFIT | S/CF | STFF | WFIT | S/CF | FC | |
DTA | 0.302 *** (−0.103) | 0.364 *** (−0.08) | 0.289 *** (−0.098) | 0.190 * (−0.107) | 0.319 *** (0.081) | 0.208 ** (−0.101) | 0.134 *** (−0.028) |
FC | 0.765 *** (−0.116) | 0.418 *** (−0.085) | 0.538 *** (−0.106) | ||||
Gender | 0.151 (−0.21) | −0.207 * (−0.122) | 0.095 (−0.215) | 0.088 (−0.213) | −0.280 ** (−0.123) | 0.086 (−0.215) | 0.188 *** (0.043) |
Age | 0.004 (−0.005) | −0.005 (−0.004) | −0.008 (−0.005) | 0.007 (−0.006) | −0.005 (−0.004) | −0.007 (−0.005) | −0.002 (0.001) |
Education level | −0.033 ** (−0.015) | −0.017 (−0.012) | −0.003 (−0.015) | −0.028 * (−0.015) | −0.016 (−0.012) | 0.000 (−0.015) | −0.003 (0.004) |
Orchard area | 0.299 *** (−0.062) | 0.014 (−0.05) | 0.112 * (−0.063) | 0.223 *** (−0.064) | −0.036 (−0.051) | 0.049 (−0.064) | 0.121 *** (0.017) |
Non-agricultural employment | −0.009 (−0.103) | −0.022 (−0.077) | −0.001 (−0.097) | −0.048 (−0.107) | −0.031 (−0.078) | −0.022 (−0.099) | 0.021 (0.027) |
Orchard fragmentation | −0.182 ** (−0.089) | 0.068 (−0.064) | −0.106 (−0.088) | −0.168 * (−0.091) | 0.068 (−0.064) | −0.09 (−0.089) | −0.002 (0.022) |
Government promotion | 0.459 *** (−0.142) | 0.066 (−0.087) | 0.519 *** (−0.132) | 0.296 ** (−0.149) | −0.028 (−0.089) | 0.421 *** (−0.136) | 0.234 *** (0.031) |
Whether Shaanxi Province | 0.542 ** (−0.239) | 0.610 *** (−0.151) | 0.887 *** (−0.267) | 0.461 * (−0.253) | 0.620 *** (−0.152) | 0.868 *** (−0.273) | 0.000 (0.053) |
Whether Shanxi Province | 0.661 *** (−0.235) | 0.555 *** (−0.146) | 1.932 *** (−0.247) | 0.693 *** (−0.233) | 0.590 *** (−0.147) | 1.934 *** (−0.244) | −0.093 * (0.052) |
Time-fixed effect | −0.286 (−0.272) | −0.338 * (−0.179) | −0.402 (−0.275) | −0.191 (−0.283) | −0.270 (−0.180) | −0.277 (−0.278) | −0.146 ** (0.062) |
Constant | −2.605 *** (−0.515) | 0.197 (−0.343) | −2.043 *** (−0.502) | −2.467 *** (−0.535) | 0.364 (−0.348) | −1.958 *** (−0.510) | −0.427 *** −0.119 |
Atrho21 | 0.238 *** (−0.057) | 0.194 *** (−0.058) | |||||
Atrho31 | 0.180 *** (−0.063) | 0.118 * (−0.065) | |||||
Atrho32 | 0.308 *** (−0.061) | 0.276 *** (−0.061) | |||||
Wald chi2(F) | 293.44 | 364.79 | 26.62 | ||||
Prob > chi2(F) | 0.000 | 0.000 | 0.000 |
Matching Method | ATT | ||
---|---|---|---|
STFF | WFIT | S/CF | |
Nearest neighbor matching | 0.172 (0.028) | 0.670 *** (0.041) | 0.214 (0.033) |
Radius matching | 0.173 ** (0.022) | 0.671 *** (0.031) | 0.214 ** (0.024) |
Kernel matching | 0.173 ** (0.028) | 0.671 *** (0.031) | 0.215 ** (0.033) |
Local linear regression matching | 0.173 ** (0.051) | 0.673 *** (0.044) | 0.215 ** (0.035) |
Mahalanobis matching | 0.175 ** (0.028) | 0.671 ** (0.037) | 0.214 (0.029) |
Variables | STFF | WFIT | S/CF | |||
---|---|---|---|---|---|---|
(1) | (2) | (1) | (2) | (1) | (2) | |
DTA | 1.0001 *** (0.379) | 1.270 *** (0.250) | 1.047 *** (0.350) | |||
Online shopping experience | 0.221 *** (0.027) | 0.221 *** (0.027) | 0.221 *** (0.027) | |||
Control variables | Controlled | Controlled | Controlled | Controlled | Controlled | Controlled |
lnsig_2 | −0.794 *** (0.020) | −0.794 *** (0.020) | −0.794 *** (0.020) | |||
atanhrho_12 | −0.414 * (0.213) | −0.506 *** (0.157) | −0.436 ** (0.200) |
Variables | Multivariateprobit3-Primary School | Multivariateprobit4-Junior High School | Multivariateprobit5-High School | ||||||
---|---|---|---|---|---|---|---|---|---|
STFF | WFIT | S/CF | STFF | WFIT | S/CF | STFF | WFIT | S/CF | |
DTA | 0.351 * (−0.183) | 0.212 (−0.134) | 0.205 (−0.178) | 0.097 (−0.161) | 0.437 *** (−0.122) | 0.294 * (−0.152) | 0.117 (0.277) | 0.237 (0.197) | −0.019 (0.243) |
FC | 0.871 *** (−0.194) | 0.458 *** (−0.143) | 0.602 *** (−0.184) | 0.750 *** (−0.176) | 0.436 *** (−0.129) | 0.495 *** (−0.161) | 0.707 ** (0.310) | 0.416 ** (0.205) | 0.453 * (0.260) |
Constant | −1.143 (−0.865) | 0.513 (−0.577) | −2.106 ** (−0.834) | −2.151 * (−1.298) | 0.667 (−0.845) | 5.221 (−2.174) | −4.098 ** (1.622) | −0.289 (0.943) | −0.861 (0.654) |
Control variables | controlled | controlled | controlled | controlled | controlled | controlled | controlled | controlled | controlled |
Atrho21 | 0.083 (−0.100) | 0.092 (−0.086) | 0.285 ** (0.144) | ||||||
Atrho31 | 0.032 (−0.132) | 0.142 (−0.112) | 0.418 *** −0.16 | ||||||
Atrho32 | 0.269 ** (−0.109) | 0.285 *** (−0.091) | 0.418 *** (0.160) | ||||||
Wald chi2 | 146.70 | 183.62 | 59.49 | ||||||
Prob > chi2 | 0.000 | 0.000 | 0.004 | ||||||
N | 441 | 561 | 214 |
Variables | Multivariateprobit6-Small Scale | Multivariateprobit7-Large Scale | ||||
---|---|---|---|---|---|---|
STFF | WFIT | S/CF | STFF | WFIT | S/CF | |
DTA | 0.166 (0.181) | 0.211 * (0.128) | 0.315 ** (0.160) | 0.228 * (0.136) | 0.390 *** (0.106) | 0.171 (0.134) |
FC | 0.942 *** (0.197) | 0.423 *** (0.127) | 0.743 *** (0.169) | 0.750 *** (0.151) | 0.429 *** (0.120) | 0.387 *** (0.144) |
Constant | −2.980 ** (0.985) | −0.517 (0.593) | −2.397 ** (0.929) | −2.416 *** (0.690) | 1.112 ** (0.481) | −2.033 *** (0.677) |
Control variables | controlled | controlled | controlled | controlled | controlled | controlled |
Atrho21 | 0.074 (0.094) | 0.242 *** (0.078) | ||||
Atrho31 | 0.138 (0.114) | 0.073 (0.086) | ||||
Atrho32 | 0.184 * (0.094) | 0.305 *** (0.082) | ||||
Wald chi2 | 186.23 | 222.21 | ||||
Prob > chi2 | 0.000 | 0.000 | ||||
N | 534 | 682 |
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Peng, X.; Yan, X.; Wang, H. Study on the Effect of Digital Technology Adoption and Farmers’ Cognition on Fertilizer Reduction and Efficiency Improvement Behavior. Agriculture 2024, 14, 973. https://doi.org/10.3390/agriculture14070973
Peng X, Yan X, Wang H. Study on the Effect of Digital Technology Adoption and Farmers’ Cognition on Fertilizer Reduction and Efficiency Improvement Behavior. Agriculture. 2024; 14(7):973. https://doi.org/10.3390/agriculture14070973
Chicago/Turabian StylePeng, Xinhui, Xiaohuan Yan, and Hongmei Wang. 2024. "Study on the Effect of Digital Technology Adoption and Farmers’ Cognition on Fertilizer Reduction and Efficiency Improvement Behavior" Agriculture 14, no. 7: 973. https://doi.org/10.3390/agriculture14070973