Beyond Awareness: Structural factors associated with adoption entry, breadth, and intensity of feed technologies in Madagascar’s smallholder livestock systems

Dataset summary

This dataset was developed to examine awareness, adoption and intensity of use of livestock feed technologies among smallholder farming households in Madagascar. Its purpose is to support analysis of the household, farm and institutional factors associated with farmers’ entry into technology adoption, the number of feed technologies adopted and the intensity with which those technologies are used.

The dataset contains cross-sectional, household-level survey data from 120 livestock-producing households. The observations cover five agroecological and administrative groupings: Sava, Vakinankaratra, Vatovavy–Fitovinany, Atsimo Andrefana and Boeny. Within these areas, data were collected from 10 districts and 10 Fokontany, with 12 households represented in each Fokontany.

The dataset includes information on household and farm characteristics, including the age, gender and education of the household head, ethnicity, membership in farmer or community organisations, landholding size, livestock ownership expressed in Tropical Livestock Units, distance to markets, availability of crop–livestock inputs and access to credit.

It also documents respondents’ awareness, use and level of use of eight livestock feed technologies:

- Dual-purpose crops
- Cultivated forage crops
- Chopping and grinding of feed materials
- Silage making
- Hay making
- Drying and storage of feed materials in bags - Urea treatment of crop residues
- Ration formulation

For each technology, awareness and use are recorded as binary variables, while level of use is measured on an ordinal scale ranging from no use to intensive integration. The dataset also contains derived indicators measuring the total number of technologies used, the household awareness index and overall utilization intensity, combining the breadth and depth of technology use.
The dataset can be used to investigate patterns of feed-technology awareness and adoption, compare adoption across regions and technologies, and assess associations between technology uptake and household resources, market access, input availability, credit access and other structural conditions. Because the data are cross-sectional and the households were purposively selected, the dataset is most appropriate for descriptive and associational analyses rather than causal inference or nationally representative estimates.