İki yeni ÇÖKV yaklaşımı PODER ve V-PARS: Paris ve İstanbul'da mikromobilite modlarının değerlendirilmesi

Distance-based Multi-Criteria Decision Making (MCDM) methods offer a robust framework for evaluating and ranking alternatives under conditions of conflicting criteria. These methods, as documented in existing literature, analyze alternatives based on their distances to reference points like positive, average, or negative ideal solutions. However, a notable gap exists in the literature – the absence of a technique where the reference point is the decision itself. While distance-based methods necessitate careful selection of distance metrics and reference points, their conceptual simplicity, visual appeal, and adaptability make them valuable tools for tackling complex decision problems across various academic disciplines. These methods are limited by their focus on distance to some reference points, neglecting the potential of self referencing and vector-based approaches in MCDM. Vectors, encompassing both magnitude (distance) and direction, are suitable for similarity operations and provide a richer understanding of an alternative's positioning within the criteria space. This doctoral thesis addresses this gap by proposing two novel MCDM procedures. The first, named POndération sur la Distance par ExtRaction (PODER), is a novel distance-based methodology designed for criteria weighting. The second, named Vector-Based Preference Ranking System (V-PARS), is a novel vector-based ranking methodology. The proposed methodologies integrate the concept of criterion extraction distance on Euclidean environment and a vectorial expansion of ideas from Social Choice Theory, specifically the Borda Count, Kemeny-Young Approach and Copeland Method. Additionally, a novel decision gathering procedure for both approaches is constructed based on Nudge Theory, which posits that individuals make better decisions when subtly guided towards a preferred outcome. This research also explores the intricacies of normalization and scaling within the context of MCDM methodologies, employing both precise and imprecise data formats (e.g. crisp and fuzzy). The proposed MCDM framework leverages this principle by incorporating both objective and subjective data to evaluate the relative suitability of alternatives. The presented choice architecture serves as a suitable framework for establishing an evaluation system centered on decision positions. The effectiveness of the proposed hybrid procedure is demonstrated by applying it to the evaluation of micromobility modes. The rising popularity of micromobility options like scooters and e-bikes has introduced new complexities in urban transportation planning. Evaluating the micromobility vehicles for specific contexts, such as city districts, requires a comprehensive and systematic approach. The proposed methodologies are applied to a case study assessing micromobility modes for Paris/France and Istanbul/Turkey, within the context of the European Union's 2050 targets. By considering the unique characteristics of each device, the methodologies identify criteria weights and preference rankings of micromobility vehicles for specific areas, contributing to informed and sustainable micromobility decisions.