An Intelligent Group Decision Support System for Urban Tourists: Development and evaluation of a well-structured group decisionmaking process

Abstract

When a group decides to plan and organize a vacation, many researchers mention that group decision making within the travel planning problem often leads to suboptimal decisions. This can be explained by the fact that the process of travel group decision making is typically ineffective. To overcome some of the problems, we propose an intelligent Group Decision Support System named Trip.Easy that creates synergy between human and machine intelligence in order to improve group decision making. The objective of this study is to develop a prototype of the Trip.Easy GDSS that combines a well-structured decision process with domain knowledge and an intelligent recommendation mechanism that facilitates reaching a consensus for the group trip planning problem. As a result, a well-designed group decision process is provided that (i) facilitates users and makes them aware of all interesting outcomes by providing intelligent recommendations, (ii) supports collaboration at a distance, (iii) minimizes irrational acts due to various influences and (iv) facilitates effective communication by means of a clear and fair process that converges to an outcome that satisfies all group members. Subsequently, a structured experiment has been designed and conducted to empirically acquire measurements of users’ satisfaction for the designed group decision process. A total of 120 participants, divided into 30 groups, were invited for the experiment. Each group was instructed to organize a city trip while using the Trip.Easy GDSS. After each session, the participants were asked to fill in a questionnaire. Analysis of the data showed that users were satisfied with the decision process of Trip.Easy GDSS. Users perceived the interaction through the graphical user interface with the Trip.Easy GDSS during the decision process as user-friendly. Furthermore, users valued the process as fair. Based upon these findings, we may conclude that the proposed group decision process that is integrated in the Trip.Easy GDSS prototype is able to facilitate users to converge towards a satisfying travel destination.MKEMan-Machine Interaction groupElectrical Engineering, Mathematics and Computer Scienc