The representation of attributes in choice experiments has significant implications for valuation as well as forecasting as attributes represented in a manner not easily understood by the respondents can affect their decision making.  This paper examines the effect of different methods of attribute representation on preference uncertainty.

A Stated Preference (SP) survey was conducted to evaluate the importance of apartment characteristics in residential choice in the Telheiras area of Lisbon.  Different levels of noise, sunlight, view and housing service charge were offered to the respondents to evaluate the impact of these on residential choice.  The SP survey was classified into two independent experiments with different representations of noise, sunlight and view.  In the first experiment, these attributes were represented using the location method while linguistic representation was used in the second experiment.  For the two experiments, binary choices as well as five point Likert scale was offered to capture preference uncertainty.

Nested logit and Error Components model are used to analyse the responses gathered from the five point Likert scale while binary logit model is used for the binary choices.  The results obtained from these models are compared across the two experiments to analyse the effect of different attribute representation techniques on respondent preference uncertainty.