database can be helpful in detecting what has happened
in the dairy herd. A typical example is a cross sectional
study of number of mastitis treatments per cow. This
may reveal that number of treatments per cow decreases
with increasing herd size, and the skilled researcher is
able to come up with some possible explanations. However,
the study also leaves the researcher with a lot of
new questions, e.g.: “What are the economic implications
of this finding?” “To what extent do managerial
differences influence the number of treatments?” and
“Can the findings be explained by the social interactions
among the people at the farm?”
Thus, although studies of cattle databases are helpful
in establishing how (mainly) biological variables are
related, expanding the analysis to other perspectives and
methodological approaches may help us better understand
why variables interact. The purpose of this paper
is to present three perspectives that may supplement the
biological perspective in agricultural and veterinary
research; the economic-, the managerial-, and the social
perspective. We review recent studies applying these
perspectives (see Table 1 for a brief overview), provide
some illustrative examples of how the perspectives can
be combined with the biological perspective, and discuss