Table 5.
Main effects mixed multinomial logit model in WTP space
| Attribute | Attribute level | Whole sample | Kilifi | Bungoma | |||
| β | SE | β | SE | β | SE | ||
| ASC | ASC | Ref. (0) | |||||
| ASC µ | 0.015 | 0.405 | 0.905 | 1.118 | −0.461 | 0.255 | |
| ASC σ | 0.516 | 0.268 | −0.293 | 2.632 | −0.355 | 0.194 | |
| Recognition | Recognition at community level | Ref. (0) | |||||
| Recognition at facility µ | 0.025 | 0.398 | −1.004 | 1.056 | 0.746 | 0.418 | |
| Recognition at facility σ | 2.821** | 0.771 | 3.672* | 1.446 | −2.250** | 0.358 | |
| Award mechanism for best performing CHV µ | 1.060** | 0.375 | 1.169 | 0.841 | 0.769* | 0.328 | |
| Award mechanism for best performing CHV σ | 2.999** | 0.636 | 4.261* | 1.648 | −1.816** | 0.182 | |
| Transport | Bicycles for CHV | Ref. (0) | |||||
| Motorcycle for CHV/CU µ | 4.805* | 0.819 | 5.917* | 2.481 | 3.913** | 0.338 | |
| Motorcycle for CHV/CU σ | 4.271** | 0.972 | 6.047** | 1.916 | 2.524** | 0.337 | |
| Motorcycle for CHEW and bicycle for CHV µ | −0.183 | 0.677 | 1.755 | 1.984 | −1.317** | 0.381 | |
| Motorcycle for CHEW and bicycle for CHV σ | 0.776 | 0.630 | −0.859 | 1.290 | 1.188** | 0.185 | |
| Tools of trade | Supplies and commodities+non-pharmaceutical+job aids/IEC materials | Ref. (0) | |||||
| Supplies and commodities+non-pharmaceutical+job aids/IEC materials+identification µ | −2.514** | 0.657 | −3.551** | 1.341 | −1.504** | 0.315 | |
| Supplies and commodities+non-pharmaceutical+job aids/IEC materials+identification σ | −0.317 | 0.483 | −0.098 | 0.465 | −0.563* | 0.284 | |
| Supplies and commodities+non-pharmaceutical+job aids/IEC materials+identification+safety gears µ | −4.281** | 1.131 | −6.935** | 2.428 | −2.173** | 0.348 | |
| Supplies and commodities+non-pharmaceutical+job aids/IEC materials+identification+safety gears σ | 2.009** | 0.640 | 2.824 | 1.473 | 1.297** | 0.209 | |
| IGA | KES 100 000 | Ref. (0) | |||||
| KES 150 000 µ | 0.190 | 0.224 | 0.164 | 0.607 | 0.217 | 0.148 | |
| KES 150 000 σ | 0.159 | 0.353 | −0.486 | 1.937 | 0.025 | 0.136 | |
| Monthly stipend (thousands of KES) | Monthly stipend µ | 0.715* | 0.302 | 0.449 | 0.399 | 2.001 | 1.342 |
| Monthly stipend σ | 0.524 | 0.439 | 0.212 | 0.675 | 2.916 | 3.664 | |
| Decision makers | 211 | 109 | 102 | ||||
| Observations | 5064 | 2616 | 2448 | ||||
| Log likelihood | −1099.937 | −559.880 | −525.174 | ||||
| Akaike’s information criterion | 2235.874 | 1155.759 | 1086.348 | ||||
| Bayesian information criterion | 2353.412 | 1261.409 | 1190.803 | ||||
All attributes were random and normally distributed except monthly stipend which was restricted to a lognormal distribution. WTP values and monthly stipend are in thousands of KES. Statistical significance: **at 0.01 level, *at 0.05 level. β is the coefficient, SE is the robust SE, µ is the mean, σ is the SD and ASC is alternative specific constant for alternative. All models used 1000 Halton draws
ASC, alternative specific constant; CHEW, community health extension worker; CHV, community health volunteer; CU, community unit; IEC, information, education and communication; IGA, income-generating activities; WTP, willingness to pay.