The Impact of Digital Literacy on Farmers’ Green Production Behavior: Mediating Effects Based on Ecological Cognition
Abstract
:1. Introduction
2. Theoretical Analysis and Research Hypothesis
3. Materials and Methods
3.1. Data Source
3.2. Variable Selection
3.3. Econometric Model
4. Estimation Results and Analysis
4.1. The Baseline Estimation Results
4.2. Main Results Based on IV Regression
4.3. Robustness Check
4.4. Main Results Based on Mediating Effect Regression
5. Discussion
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Variable | Definition | Value |
---|---|---|
Hazard Cognition | Failure to treat the seed before sowing increases the risk of microbial damage. | Strongly Disagree = 1, Disagree = 2, Fairly = 3, Agree = 4, Strongly Agree = 5 |
Insecticides penetrate the tissue and remain on the vegetables. | ||
Excessive use of chemical fertilizers can lead to higher nitrate content in vegetables. | ||
Non-compliant use of pesticides and fertilizers can leave residues on vegetables that are harmful to human health. | ||
Non-compliant use of pesticides and fertilizers can pollute the ecosystem. | ||
No use of banned pesticides, or fertilizers. | ||
Waste chemicals can pollute the ecosystem if not disposed of properly. | ||
Behavioral Cognition | I am willing to choose a regular farm store to buy insecticides. | |
I am willing to accept the technical specifications of the agricultural technician. | ||
I would choose to regulate the application of pesticides and fertilizers according to the instructions. | ||
I am willing to enforce strict safety intervals for pesticides. | ||
I am willing to aseptically treat the seeds before planting. | ||
I am willing to use water-saving irrigation techniques, and pest and disease biological control techniques. | ||
I am willing to properly dispose of discarded pesticide and fertilizer packaging, etc. | ||
Earnings Cognition | Adoption of green production techniques will reduce ecological pollution. | |
Applying chemicals such as pollution-free pesticides can reduce human health hazards. | ||
Safe use of pesticides and fertilizers is more important than control effectiveness. | ||
Adoption of green production technologies can help promote low-carbon agriculture. | ||
Adoption of green production technologies can contribute to carbon neutrality and peak carbon. | ||
The application of chemicals such as pollution-free pesticides can improve economic incomes. | ||
The adoption of green production techniques produces safer agricultural products. |
Variable | Hazard Cognition | Behavioral Cognition | Earnings Cognition | |
---|---|---|---|---|
Number of variable items | 7 | 7 | 7 | |
Cronbach’s alpha coefficient | 0.8299 | 0.8409 | 0.8829 | |
KMO value | 0.836 | 0.831 | 0.886 | |
Bartlett’s sphericity test | Chi-square | 2225.732 | 2524.742 | 3176.121 |
Degrees of freedom | 21 | 21 | 21 | |
Significance level | 0.000 | 0.000 | 0.000 |
Variable | Definition | Mean | SD |
---|---|---|---|
Green production behavior | Measured based on the cumulative extent of use of green agricultural technologies, aseptic seed treatment, soil-formula fertilization technology, pest and disease biological control technology, water-saving irrigation technology, and waste packaging treatment | 2.67 | 1.08 |
Digital learning literacy | The frequency of using the Internet for learning. Never = 1, rarely = 2, sometimes = 3, often = 4, and very often = 5 | 2.08 | 0.88 |
Digital social literacy | The frequency of using the Internet for socializing. Never = 1, rarely = 2, sometimes = 3, often = 4, and very often = 5 | 1.61 | 0.93 |
Digital transaction literacy | The frequency of using the Internet for selling. Never = 1, rarely = 2, sometimes = 3, often = 4, and very often = 5 | 2.72 | 1.03 |
Age | Year | 55.04 | 11.27 |
Gender | Male = 1, female = 0 | 0.57 | 0.50 |
Health | Poor = 1, fair = 2, good = 3, very good = 4, excellent = 5 | 2.92 | 1.08 |
Education | Illiterate = 1, primary school = 2, junior middle school = 3, high school and above = 4 | 1.95 | 0.78 |
Accessibility of villages | Yes = 1, no = 0 | 0.83 | 0.37 |
Political profile | Party members = 1, non-members = 0 | 0.10 | 0.30 |
Number of laborers | Count | 4.11 | 1.76 |
Village economy | Well below average = 1, below average = 2, average = 3, above average = 4, well above average = 5 | 2.80 | 0.99 |
Use of agricultural machinery | yes = 1, no = 0 | 0.52 | 0.50 |
Perceived risk | Health risk, environmental risk, disaster risk, cultivation risk, and lending risk. Of these risks, how many can be perceived, and what values are assigned | 2.65 | 1.01 |
Land size | Below 0.33(ha) = 1, 0.33–0.67(ha) = 2, 0.67–1(ha) = 3, 1–1.33(ha) = 4, above 1.33(ha) = 5 | 2.69 | 1.31 |
Membership in cooperatives | Knowledge, normative techniques, social relations, subsidies, and regulation. How many can be acquired, and what values are assigned | 3.00 | 1.18 |
Ecological cognition | Measured by validated factor analysis | 0.00 | 0.76 |
Region | Shenyang, yes = 1, no = 0; Liaoyang, yes = 1, no = 0; Panjin, yes = 1, no = 0; Dandong, yes = 1, no = 0 |
Variable | OLS (1) | OLS (2) | OLS (3) | Ordered Logit (4) | Ordered Logit (5) | Ordered Logit (6) |
---|---|---|---|---|---|---|
Digital learning literacy | 0.1987 *** (0.0379) | 0.4032 *** (0.0923) | ||||
Digital social literacy | 0.1592 *** (0.0314) | 0.3621 *** (0.0715) | ||||
Digital transaction literacy | 0.2416 *** (0.0485) | 0.6262 *** (0.1404) | ||||
Education | 0.0608 ** (0.0277) | 0.0700 ** (0.0281) | 0.0732 *** (0.0279) | 0.1183 * (0.0631) | 0.1240 * (0.0635) | 0.1294 ** (0.0632) |
Membership in cooperatives | 0.1034 *** (0.0376) | 0.0846 ** (0.0378) | 0.0755 ** (0.0372) | 0.2693 *** (0.0872) | 0.2390 *** (0.0869) | 0.2143 ** (0.0862) |
Perceived risk | 0.4590 *** (0.0327) | 0.4401 *** (0.0332) | 0.3682 *** (0.0423) | 1.0539 *** (0.0888) | 1.0222 *** (0.0874) | 0.8103 *** (0.1145) |
Village economy | 0.1333 *** (0.0277) | 0.1389 (0.0280) | 0.1238 *** (0.0286) | 0.2224 ** (0.1075) | 0.2006 * (0.1068) | 0.1681 (0.1076) |
Age | −0.0024 (0.0029) | −0.0031 (0.0029) | −0.0026 (0.0029) | −0.0065 (0.0065) | −0.0076 (0.0066) | −0.0056 (0.0064) |
Gender | −0.0499 (0.0574) | −0.0538 (0.0574) | −0.0661 (0.0567) | −0.1094 (0.1306) | −0.1228 (0.1296) | −0.1521 (0.1285) |
Health | 0.0269 (0.0324) | 0.0277 (0.0323) | −0.0063 (0.0315) | 0.0181 (0.0765) | 0.0222 (0.0751) | −0.0657 (0.0742) |
Political profile | 0.0400 (0.0806) | 0.0647 (0.0807) | 0.0659 (0.0805) | 0.0551 (0.1870) | 0.1015 (0.1833) | 0.1198 (0.1829) |
Number of laborers | −0.0208 (0.0167) | −0.0310 * (0.0167) | −0.0253 (0.0166) | −0.0506 (0.0381) | −0.0622 * (0.0374) | −0.0452 (0.0378) |
Use of agricultural machinery | 0.0619 (0.0574) | 0.0596 (0.0577) | 0.0783 (0.0572) | 0.1897 (0.1311) | 0.1873 (0.1303) | 0.2289 * (0.1296) |
Accessibility of villages | 0.0264 (0.0880) | 0.0345 (0.0910) | 0.0291 (0.0858) | −0.0419 (0.2031) | −0.0582 (0.2046) | −0.0342 (0.1991) |
Land size | −0.0115 (0.0421) | −0.0228 (0.0430) | −0.0083 (0.0414) | −0.0441 (0.0986) | −0.0606 (0.1005) | −0.0254 (0.0952) |
Constant | 0.3368 (0.2695) | 0.6219 ** (0.2603) | 0.5170 ** (0.2620) | - | - | - |
Observations | 884 | 884 | 884 | 884 | 884 | 884 |
R2/pseudo R2 | 0.39 | 0.39 | 0.40 | 0.16 | 0.16 | 0.17 |
Variable | Model (1) First Stage | Model (1) Second Stage | Model (2) First Stage | Model (2) Second Stage | Model (3) First Stage | Model (3) Second Stage |
---|---|---|---|---|---|---|
Digital learning literacy | 0.9678 *** (0.2702) | |||||
Digital social literacy | 1.0368 *** (0.2397) | |||||
Digital transaction literacy | 0.7835 *** (0.1688) | |||||
Digital learning literacy-IV | 0.2114 *** (0.0418) | |||||
Digital social literacy-IV | 0.0968 *** (0.0169) | |||||
Digital transaction literacy-IV | 0.3391 *** (0.0393) | |||||
Control | YES | YES | YES | YES | YES | YES |
Constant | 1.8999 *** (0.2491) | −1.0483 * (0.5658) | 0.5007 ** (0.2559) | 0.3985 (0.3404) | 1.1178 *** (0.2369) | 0.1107 (0.2953) |
F-Statistics | 23.0400 | 43.3641 | 26.1300 | 30.9648 | 54.4185 | 32.1259 |
p-Value | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 |
Observations | 884 | 884 | 884 | 884 | 884 | 884 |
Variable | Match Stats | Treatment Group | Control Group | Bias (%) | Reducing Bias (%) | T-Value | p-Value |
---|---|---|---|---|---|---|---|
Age | pre-match | 54.883 | 55.125 | −2.2 | −209.6 | −0.31 | 0.758 |
post-match | 54.883 | 54.133 | 6.7 | 0.88 | 0.378 | ||
Gender | pre-match | 0.562 | 0.570 | −1.6 | −251.0 | −0.23 | 0.819 |
post-match | 0.562 | 0.590 | −5.6 | −0.71 | 0.475 | ||
Education | pre-match | 1.994 | 1.921 | 9.3 | 95.7 | 1.34 | 0.181 |
post-match | 1.994 | 1.997 | −0.4 | −0.05 | 0.959 | ||
Number of laborers | pre-match | 3.741 | 4.318 | −33.6 | 93.0 | −4.76 | 0.000 |
post-match | 3.741 | 3.701 | 2.3 | 0.31 | 0.756 | ||
Use of agricultural machinery | pre-match | 0.565 | 0.495 | 14.1 | 86.8 | 2.01 | 0.044 |
post-match | 0.565 | 0.556 | 1.9 | 0.24 | 0.813 | ||
Accessibility of villages | pre-match | 0.827 | 0.838 | −2.8 | 40.3 | −0.40 | 0.691 |
post-match | 0.827 | 0.821 | 1.7 | 0.21 | 0.837 | ||
Political profile | pre-match | 0.256 | 0.161 | 23.6 | 90.3 | 3.47 | 0.001 |
post-match | 0.256 | 0.247 | 2.3 | 0.27 | 0.786 |
Variable | Match Stats | Treatment Group | Control Group | Bias (%) | Reducing Bias (%) | T-Value | p-Value |
---|---|---|---|---|---|---|---|
Age | pre-match | 54.678 | 55.373 | −6.2 | 17.8 | −0.92 | 0.360 |
post-match | 54.763 | 55.335 | −5.1 | −0.72 | 0.469 | ||
Gender | pre-match | 0.577 | 0.557 | 4.0 | −4.9 | 0.60 | 0.548 |
post-match | 0.578 | 0.557 | 4.2 | 0.62 | 0.535 | ||
Education | pre-match | 1.981 | 1.917 | 8.3 | 89.1 | 1.24 | 0.216 |
post-match | 1.977 | 1.984 | −0.9 | −0.13 | 0.896 | ||
Number of laborers | pre-match | 4.220 | 4.000 | 12.5 | 85.1 | 1.86 | 0.064 |
post-match | 4.213 | 4.180 | 1.9 | 0.27 | 0.785 | ||
Use of agricultural machinery | pre-match | 0.556 | 0.487 | 13.9 | 66.2 | 2.06 | 0.040 |
post-match | 0.555 | 0.532 | 4.7 | 0.69 | 0.493 | ||
Accessibility of villages | pre-match | 0.829 | 0.838 | −2.2 | −98.0 | −0.33 | 0.741 |
post-match | 0.829 | 0.813 | 4.4 | 0.62 | 0.533 | ||
Political profile | pre-match | 0.217 | 0.175 | 10.5 | −0.7 | 1.57 | 0.117 |
post-match | 0.215 | 0.258 | −8.6 | −1.45 | 0.148 |
Variable | Match Stats | Treatment Group | Control Group | Bias (%) | Reducing Bias (%) | T-Value | p-Value |
---|---|---|---|---|---|---|---|
Age | pre-match | 54.873 | 55.288 | −3.7 | 2.1 | −0.53 | 0.593 |
post-match | 54.873 | 54.467 | 3.6 | 0.57 | 0.571 | ||
Gender | pre-match | 0.575 | 0.553 | 4.5 | −17.9 | 0.65 | 0.518 |
post-match | 0.575 | 0.601 | −5.3 | −0.87 | 0.386 | ||
Education | pre-match | 1.972 | 1.911 | 7.9 | 9.0 | 1.15 | 0.251 |
post-match | 1.972 | 2.028 | −7.2 | −1.14 | 0.253 | ||
Number of laborers | pre-match | 4.048 | 4.196 | −8.4 | 95.0 | −1.22 | 0.223 |
post-match | 4.048 | 4.041 | 0.4 | 0.07 | 0.944 | ||
Use of agricultural machinery | pre-match | 0.546 | 0.481 | 12.9 | 79.7 | 1.87 | 0.062 |
post-match | 0.546 | 0.533 | 2.6 | 0.43 | 0.671 | ||
Accessibility of villages | pre-match | 0.838 | 0.827 | 2.9 | −207.5 | 0.42 | 0.691 |
post-match | 0.838 | 0.804 | 9.0 | 1.43 | 0.152 | ||
Political profile | pre-match | 0.209 | 0.176 | 8.3 | 48.9 | 1.20 | 0.231 |
post-match | 0.209 | 0.192 | 4.3 | 0.69 | 0.493 |
Variable | Farmers’ Green Production Behavior | ||
---|---|---|---|
ATT | Standard Errors | t-Value | |
Digital learning literacy | 0.392 *** | 0.108 | 3.615 |
Digital social literacy | 0.375 *** | 0.092 | 4.091 |
Digital transaction literacy | 0.832 *** | 0.090 | 9.240 |
Variable | Digital Learning Literacy | Digital Social Literacy | Digital Transaction Literacy |
---|---|---|---|
Total effect (a1) | 0.1987 *** (0.0340) | 0.1592 *** (0.0334) | 0.2416 *** (0.0350) |
Effect of digital literacy on ecological cognition (b1) | 0.3988 *** (0.0668) | 0.3658 *** (0.0653) | 0.4695 *** (0.0688) |
Effect of ecological cognition on farmers’ green production behavior (c2) | 0.0831 *** (0.0170) | 0.0873 *** (0.0171) | 0.0772 *** (0.0170) |
Direct effect (c1) | 0.1655 *** (0.0343) | 0.1273 *** (0.0335) | 0.2054 *** (0.0355) |
Mediating effect (b1 c2)/bootstrap test value | 0.0331 *** (0.0088) | 0.0319 *** (0.0085) | 0.0362 *** (0.0096) |
Mediating effect share (b1 c2/a1) (%) | 16.6783 | 20.0589 | 14.9977 |
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© 2024 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/).
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Liu, X.; Wang, Z.; Han, X. The Impact of Digital Literacy on Farmers’ Green Production Behavior: Mediating Effects Based on Ecological Cognition. Sustainability 2024, 16, 7507. https://doi.org/10.3390/su16177507
Liu X, Wang Z, Han X. The Impact of Digital Literacy on Farmers’ Green Production Behavior: Mediating Effects Based on Ecological Cognition. Sustainability. 2024; 16(17):7507. https://doi.org/10.3390/su16177507
Chicago/Turabian StyleLiu, Xiao, Zhenyu Wang, and Xiaoyan Han. 2024. "The Impact of Digital Literacy on Farmers’ Green Production Behavior: Mediating Effects Based on Ecological Cognition" Sustainability 16, no. 17: 7507. https://doi.org/10.3390/su16177507