A group consensus-based travel destination evaluation method with online reviews

Abstract

With the help of the massive online information, non-expert decision-making problems (such as travel destination selection) can be solved. Online reviews provide decision-making opinions and weight information for tourists who have never been to the alternative travel destinations. To deal with the increasing tourism products and group tourists, this study proposes a novel group consensus-based travel destination evaluation method with online reviews, which considers the missing preference estimating and group consensus reaching process. Firstly, decision opinions are represented through the sentiment matrix with the percentage distribution. Secondly, to obtain the weight vector of attributes, the incomplete complementary matrices with the preference of attributes are given by group users. Subsequently, the missing preference values in the matrix are estimated. Thirdly, all users are required to reach group consensus based on the minimum adjustment cost feedback mechanism. Finally, the sentiment matrix with the percentage distribution can be aggregated by the weight vectors. So that the ranking of alternatives can be obtained. In this study, an example of travel destination evaluation based on the online reviews of Dazhong.com and Ctrip.com is given to illustrate the use of the proposed method.