TY - JOUR
T1 - Preferences for enhanced seasonal weather and climate services among maize farmers in Zimbabwe
T2 - A choice experiment analysis
AU - Manzvera, Joseph
AU - Anaman, Kwabena Asomanin
AU - Mensah-Bonsu, Akwasi
AU - Barimah, Alfred
N1 - Publisher Copyright:
© 2025 The Author(s). Meteorological Applications published by John Wiley & Sons Ltd on behalf of Royal Meteorological Society.
PY - 2025/3/1
Y1 - 2025/3/1
N2 - Using a discrete choice experiment, this article analyzed maize farmers' stated preferences for seasonal weather forecast attributes in Zimbabwe. Specifically, the study assessed the most preferred attributes of modern seasonal weather forecasts to guide investment priorities. The mixed logit model, which accounts for taste heterogeneity, was employed to analyze the data. The results show that maize farmers place positive utility on downscaling forecasts to the village level, bundling with agronomic advisory information, and a long lead time of 6 months ahead of the onset of the rainy season. Farmers are willing to pay 1.40 United States dollars (US$) for downscaling seasonal forecasts to the village level, US$1.50 for bundling seasonal weather forecasts with agronomic information such as suitable crop varieties to grow, and US$1.80 for disseminating seasonal forecasts with 6 months lead time. The marginal willingness to pay estimates translate to US$368 million economic value of modern seasonal weather forecasts per annum for all maize farmers in Zimbabwe. These findings underscored the importance attached to seasonal weather forecasts by farmers as a valuable decision-support service. Therefore, this study presents a compelling case for increasing national resource allocation towards the production and delivery of location-specific seasonal weather with a six-month lead time and bundling the forecasts with agronomic advisory information. Co-production of seasonal weather forecasts and integrating them with indigenous seasonal weather forecasts, as well as disseminating forecasts via mobile applications, could also be explored in addition to radio stations and extension agents. Public–private partnerships with private-sector players, such as telecommunication companies, could help to digitalize seasonal weather forecast dissemination.
AB - Using a discrete choice experiment, this article analyzed maize farmers' stated preferences for seasonal weather forecast attributes in Zimbabwe. Specifically, the study assessed the most preferred attributes of modern seasonal weather forecasts to guide investment priorities. The mixed logit model, which accounts for taste heterogeneity, was employed to analyze the data. The results show that maize farmers place positive utility on downscaling forecasts to the village level, bundling with agronomic advisory information, and a long lead time of 6 months ahead of the onset of the rainy season. Farmers are willing to pay 1.40 United States dollars (US$) for downscaling seasonal forecasts to the village level, US$1.50 for bundling seasonal weather forecasts with agronomic information such as suitable crop varieties to grow, and US$1.80 for disseminating seasonal forecasts with 6 months lead time. The marginal willingness to pay estimates translate to US$368 million economic value of modern seasonal weather forecasts per annum for all maize farmers in Zimbabwe. These findings underscored the importance attached to seasonal weather forecasts by farmers as a valuable decision-support service. Therefore, this study presents a compelling case for increasing national resource allocation towards the production and delivery of location-specific seasonal weather with a six-month lead time and bundling the forecasts with agronomic advisory information. Co-production of seasonal weather forecasts and integrating them with indigenous seasonal weather forecasts, as well as disseminating forecasts via mobile applications, could also be explored in addition to radio stations and extension agents. Public–private partnerships with private-sector players, such as telecommunication companies, could help to digitalize seasonal weather forecast dissemination.
KW - Zimbabwe
KW - discrete choice experiment
KW - economic valuation
KW - meteorological services
KW - resource economics
KW - weather forecast attributes
UR - https://www.scopus.com/pages/publications/105001675312
U2 - 10.1002/met.70040
DO - 10.1002/met.70040
M3 - Article
AN - SCOPUS:105001675312
SN - 1350-4827
VL - 32
JO - Meteorological Applications
JF - Meteorological Applications
IS - 2
M1 - e70040
ER -