Over the past century there has been a dramatic increase in the number of road accidents in
Malaysia. Hence, it is necessary to create a decision making method which can consider various
preferences and criteria in order to identify the main causes of the accidents. This paper proposes an
Interval Type-2 Fuzzy Technique for Order Preference by Similarity to Ideal Solution (IT2FTOPSIS)
method which provides a comprehensive valuation from experts. This method is developed based on
the aggregation of experts’ opinions on preferred causes of road accidents. The extended
IT2FTOPSIS employs a linguistic scales of positive and negative Interval Type-2 Trapezoidal Fuzzy
Number (IT2TrFN) and hybrid averaging approach (from an ambiguity and type-reduction methods) to
formulate a collective decision environment. Three authorised personnel from three Malaysian
Government agencies were interviewed where they were asked to rank the causes. The analysis
shows that the linguistic scales of positive and negative Interval Type-2 Trapezoidal Fuzzy Number
(IT2TrFN) and hybrid averaging approach are effective in measuring the uncertainties in the
interviewees’ responses. Thus this paper concludes that the extended IT2FTOPSIS is more aligned
with the users’ decisions compared to the earlier IT2FTOPSIS.