Factors influencing farmers' willingness to adopt digital application tools
| Marginal effects | ||||||
|---|---|---|---|---|---|---|
| Coefficient | Standard error | t-value | dy/dx | Standard error | t-value | |
| Female | −0.466* | 0.242 | −1.92 | −0.081* | 0.041 | −1.950 |
| Age | −0.005 | 0.01 | −0.45 | −0.001 | 0.002 | −0.450 |
| Primary education | 0.591* | 0.329 | 1.79 | 0.104 | 0.059 | 1.770 |
| Secondary education | 0.762** | 0.355 | 2.15 | 0.133** | 0.063 | 2.100 |
| Tertiary education | 0.274 | 0.477 | 0.57 | 0.049 | 0.086 | 0.570 |
| Years of experience in farming | 0.021* | 0.012 | 1.80 | 0.004* | 0.002 | 1.820 |
| Training | 0.51** | 0.235 | 2.18 | 0.088** | 0.040 | 2.210 |
| Access to internet | 0.743*** | 0.241 | 3.08 | 0.129*** | 0.040 | 3.200 |
| Access to extension services | 0.15 | 0.403 | 0.37 | 0.026 | 0.070 | 0.370 |
| Awareness of the IITA herbicide calculator | 0.654** | 0.324 | 2.02 | 0.113** | 0.055 | 2.040 |
| Awareness of Akilimo | −0.779** | 0.303 | −2.57 | −0.135** | 0.051 | −2.630 |
| Ownership of smartphone | 1.64*** | 0.361 | 4.54 | 0.284*** | 0.059 | 4.860 |
| Use a paid phone application | 1.183** | 0.497 | 2.38 | 0.205** | 0.085 | 2.400 |
| Calibration spraying | 0.162 | 0.242 | 0.67 | 0.028 | 0.042 | 0.670 |
| Cost of application | 0.78*** | 0.286 | 2.73 | 0.135*** | 0.048 | 2.800 |
| Ease of use of the application | 0.274 | 0.292 | 0.94 | 0.047 | 0.050 | 0.940 |
| Innovativeness of application | −0.652 | 0.646 | −1.01 | −0.113 | 0.112 | −1.010 |
| The application used previously by other farmers | 0.599 | 0.816 | 0.73 | 0.104 | 0.141 | 0.740 |
| Constant | −1.788*** | 0.635 | −2.81 | |||
| Pseudo r-squared = 0.211 | Number of observations = 564 | |||||
| Chi-square = 155.869 | Prob > χ2 = 0.000 | |||||
| Marginal effects | ||||||
|---|---|---|---|---|---|---|
| Coefficient | Standard error | dy/dx | Standard error | |||
| Female | −0.466* | 0.242 | −1.92 | −0.081* | 0.041 | −1.950 |
| Age | −0.005 | 0.01 | −0.45 | −0.001 | 0.002 | −0.450 |
| Primary education | 0.591* | 0.329 | 1.79 | 0.104 | 0.059 | 1.770 |
| Secondary education | 0.762** | 0.355 | 2.15 | 0.133** | 0.063 | 2.100 |
| Tertiary education | 0.274 | 0.477 | 0.57 | 0.049 | 0.086 | 0.570 |
| Years of experience in farming | 0.021* | 0.012 | 1.80 | 0.004* | 0.002 | 1.820 |
| Training | 0.51** | 0.235 | 2.18 | 0.088** | 0.040 | 2.210 |
| Access to internet | 0.743*** | 0.241 | 3.08 | 0.129*** | 0.040 | 3.200 |
| Access to extension services | 0.15 | 0.403 | 0.37 | 0.026 | 0.070 | 0.370 |
| Awareness of the IITA herbicide calculator | 0.654** | 0.324 | 2.02 | 0.113** | 0.055 | 2.040 |
| Awareness of Akilimo | −0.779** | 0.303 | −2.57 | −0.135** | 0.051 | −2.630 |
| Ownership of smartphone | 1.64*** | 0.361 | 4.54 | 0.284*** | 0.059 | 4.860 |
| Use a paid phone application | 1.183** | 0.497 | 2.38 | 0.205** | 0.085 | 2.400 |
| Calibration spraying | 0.162 | 0.242 | 0.67 | 0.028 | 0.042 | 0.670 |
| Cost of application | 0.78*** | 0.286 | 2.73 | 0.135*** | 0.048 | 2.800 |
| Ease of use of the application | 0.274 | 0.292 | 0.94 | 0.047 | 0.050 | 0.940 |
| Innovativeness of application | −0.652 | 0.646 | −1.01 | −0.113 | 0.112 | −1.010 |
| The application used previously by other farmers | 0.599 | 0.816 | 0.73 | 0.104 | 0.141 | 0.740 |
| Constant | −1.788*** | 0.635 | −2.81 | |||
| Pseudo r-squared = 0.211 | Number of observations = 564 | |||||
| Chi-square = 155.869 | Prob > | |||||
Note(s): ***p < 0.01, **p < 0.05, *p < 0.1
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