  Project productivity is a key factor for producing effort estimates from Use
Case Points (UCP), especially when the historical dataset is absent. The first
versions of UCP effort estimation models used a fixed number or very limited
numbers of productivity ratios for all new projects. These approaches have not
been well examined over a large number of projects so the validity of these
studies was a matter for criticism. The newly available large software datasets
allow us to perform further research on the usefulness of productivity for
effort estimation of software development. Specifically, we studied the
relationship between project productivity and UCP environmental factors, as
they have a significant impact on the amount of productivity needed for a
software project. Therefore, we designed four studies, using various
classification and regression methods, to examine the usefulness of that
relationship and its impact on UCP effort estimation. The results we obtained
are encouraging and show potential improvement in effort estimation.
Furthermore, the efficiency of that relationship is better over a dataset that
comes from industry because of the quality of data collection. Our comment on
the findings is that it is better to exclude environmental factors from
calculating UCP and make them available only for computing productivity. The
study also encourages project managers to understand how to better assess the
environmental factors as they do have a significant impact on productivity
