Comparison of Updating Techniques in Transferability Analysis of Work Trip Mode Choice Models in Developing Countries

This study analyzes performance of updating techniques in transferability of mode choice models in developing countries. A model specification, estimated in Ho Chi Minh City, was transferred to Phnom Penh. Naive transfer and 4 updating methods associated with small sized samples were used in the transfer process and evaluated based on statistical perspective and predictive ability. The study also illustrates the problems faced in model transferability development, due to the lack of available and suitable data in Phnom Penh. This lack is strongly related to different methods and structures applied in collecting the data. Simplified approaches to the difficulties are proposed in this study. The results show that updating ASCs, updating both ASCs and scale parameter, and use of combined transfer estimators all produce significant improvement, both statistically and in predictability, in updating the model. The last 2 methods have proven to be superior to the first method, owing to the inclusion of transfer bias considerations in the estimations. However, small data samples should not have large transfer bias when using combined transfer estimators. It is also concluded that naively transfering a model is not recommended, and Bayesian updating should be avoided when transfer bias exists.

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