Abstract:
Research on demand-model transferability has consistently shown that the updated models perform better than the
simple transfer of the original model with the original coefficients. Several methods are available for the updating of
parameter estimates during model transfer. The scalar factor method has been extended to specify individual factors
for each variable This method allows the flexibility of removing insignificant variables in transfer; it also permits the
grouping of parameters that have to be updated by a common factor. Individual scalar factors can also be identified
for variables that are uniquely affected during transfer. This approach therefore incorporates the strength of both the
sample data and the calibration model to its maximum showing that this method gives excellent fit to observed flows
when tested for geographical transferability of an aggregate intercity total demand model for public transport in Sri Lanka.
It is also shown that the Bayesian method becomes less efficient when sample sizes available for updating become smaller.
