Participant Trustworthiness Analysis in the Game-Based Urban Planning Processes by Promethee-MGQNN Approach

Abstract

Serious games together with the gamified and the game-based surveys (GBS), offer an engaging way to increase citizens’ participation in urban planning projects. However, there is always the risk of untrustworthy participants, which can decrease the overall reliability of the game-based research. Trustworthiness analysis is a highly challenging task since the neuropsychology of the GBS respondents and the infinite amount of their possible in-game actions causes many uncertainties in the data analysis. The novel MCDM approach PROMETHEE-mGqNN (PROMETHEE under m-generalised q-neutrosophic numbers) is proposed in this paper as the solution to the described problem. Five criteria that might be automatically calculated from the in-game data are proposed to construct the decision matrix to identify the untrustworthy respondents. The game-based survey “Parkis” developed to assess the safety and attractiveness of the urban public park “Missionary Garden” (Vilnius, Lithuania) is proposed as the case study of this research. By applying the proposed methodology, we calculated the trustworthy index value and noticed that it is capable of detecting the behavioural tendencies of the GBS players.

Gamifying Decision Support Systems to Promote Inclusive and Engaged Urban Resilience Planning

“…More recent games build upon these concepts and provide players with additional realism and engagement through newer technologies. For example, Parkis (Baušys et al, 2021) generates realistic 3D models of real-world locations derived from GIS data. GAME4City (Fonseca et al, 2021) allows for players to interact with realistic 3D models of urban designs in a VR environment, thus providing an immersive experience in which players can gain an increased understanding of the project whilst facilitating the incorporation of user input into designs.…”

“…Additionally, through providing an alternative educational approach and learning model, DSSs can be uniquely suited to address knowledge deficits, create buy-in, break ingrained habits, and increase long-term engagement (Devisch et al, 2016;Galeote et al, 2021;Petersen et al, 2019;Ro et al, 2017). Finally, games should have real-world applications that can have beneficial impacts on local communities (Baušys et al, 2021;. A good balance of these qualities is likely to enhance user experiences by improving motivation for participation and offering an understanding of the implications, both positive and negative, of a proposed design.…”

Selection of Optimal Segmentation Algorithm for Satellite Images by Intuitionistic Fuzzy PROMETHEE Method

“…WASPAS-mGqNS [9] was utilized for ranking regions by minimizing the traveled distance and maximizing the exploration space of an autonomous robot. The mGqNN version of the PROMETHEE multi-criteria method was used to calculate the trustworthiness index of the respondents participating in a game-based survey [10]. MCDM methods have also been adapted for formulating and solving image processing problems, including segmentation.…”

M-generalised q-neutrosophic extension of CoCoSo method

“…In 2019, a notion of neutrosophic sets, which can be considered as the generalization of the following fuzzy sets: intuitionistic fuzzy (IFS), q-rung orthopair fuzzy and Pythagorean fuzzy sets was proposed by Smarandache [20]. Based on this concept, the new extensions of the classical MCDM methods, like MULTIMOORA, WASPAS, PROMETHEE [34], [18], [2], were developed by applying the environment of the m-generalized q-neutrosophic sets (mGqNSs).…”