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There are many potential factors that are involved in the decision making process of site selection, which makes it a challenging issue. This paper addresses the collaborative decision making concept through a geo-social network to predict site selection for public parking in Tehran, Iran. The presented approach utilized the analytic hierarchy process (AHP) as a multi-criteria decision method (MCDM) for weighting the criteria, which was completed in two stages; once by 50 experts, and then by three different levels of users, including 50 experts, 25 urban managers, and 150 pubic citizens, with respect to the case study area. The fuzzy majority method aggregates the archived results of AHP to determine the preferred locations that are suitable for public parking. The proposed method was implemented using a telegram bot platform. Two main advantages of the collaborative decision making scenario for public urban site selection are the fair distribution of the selected locations and the high satisfaction of users, which increased from 65% to 85%. This study presents an application for site selection based on multi-criteria decision making in a geo-social network context.

A Novel Approach to Site Selection: Collaborative Multi-Criteria Decision Making through Geo-Social Network (Case Study: Public Parking)