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    Continuous Intuitionistic Fuzzy AHP & CODAS Methodology for Automation Degree Selection
    (Old City Publishing Inc, 2024) Alkan, Nursah; Otay, Irem; Gul, Alize Yaprak; Demir, Zeynep Burcu Kizilkan; Dogan, Onur
    The automotive industry's evolution thrives on technological innovation, prioritizing efficiency, safety, and sustainability. Recent improvements in autonomous driving and IoT integration have revolutionized vehicle design, safety, and maintenance with different automation degrees from partial human control to full automation. Selecting these automation degrees involves complicated Multi-Criteria Decision-Making (MCDM) encompassing technical feasibility, societal impact, and regulatory compliance. Utilizing Analytic Hierarchy Process (AHP) and Combinative Distance-Based Assessment (CODAS) offers a structured framework to navigate these complexities. AHP establishes criteria importance, while CODAS handles uncertainties, enabling informed decisions balancing technology with ethical, societal, and regulatory considerations. Fuzzy extensions further refine these methodologies, empowering the industry to adeptly address subjective perceptions and ambiguous data, enhancing the decision-making framework for automotive technology evolution. This paper navigates the intricate landscape of automation degree selection within the automotive industry evolution, employing a structured approach merging fuzzy AHP and fuzzy CODAS methods by utilizing Continuous Intuitionistic Fuzzy Set (CINFUS). This approach not only brings a new perspective to autonomous vehicles but also highlights the importance of choosing the right automation degree. Moreover, a sensitivity analysis involved adjusting the weights assigned to different criteria within the Continuous Intuitionistic Fuzzy (CINFU) AHP framework. By systematically altering these weights and observing their impact on the final automation degree selection, decision-makers can understand the sensitivity of the chosen automation degree to changes in priority among criteria.
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    Implementing the Borda outcome via truncated scoring rules: a computational study
    (Springer, 2014) Dogan, Onur; Giritligil, Ayca Ebru
    This study is an attempt to empirically understand the likelihood of choosing the Borda outcome through a truncated scoring rule when n voters are asked to report only part of their linear preferences over m alternatives. We run Monte Carlo simulations through a grid search algorithm as we employ an impartial culture model to sample voters' preferences. Given the range of parameter values we consider, we report the truncated scoring rules that maximize the likelihood of implementing the Borda outcome and how the maximum likelihood changes with m and n. We also present our results on the relative performances of some popular truncated voting rules, such as plurality and approval voting, in implementing the Borda outcome and demonstrate that two-level approval voting performs significantly better than the plurality rule. Moreover, we propose the expected Borda rule as a good proxy for the best implementor of the Borda rule among all truncated rules.
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    Minimally strategy-proof rank aggregation
    (Springer, 2025) Dindar, Hayrullah; Dogan, Onur; Laine, Jean
    A rank aggregation rule aggregates finitely many linear orderings of objects to a collective linear ordering of these objects. We consider the robustness of rank aggregation methods to manipulation by misrepresentation of some individual order. This requires formulating assumptions about how individuals compare orders. Betweenness is a natural assumption for rank aggregation rules interpreted as Arrowian aggregation rules, which maps every family of individual preferences over social alternatives to a collective preference over those alternatives. However, many rank aggregation rules do not relate to the classical preference aggregation problem, and call for different assumptions. Instead of focusing on specific assumptions, we only assume that individuals compare orders by means of an order extension, which maps every linear order p over objects to a linear order over orders which places p at top. We define as minimally strategy-proof a rank aggregation rule that cannot be manipulated with respect to at least one order extension. We characterize the class of minimal strategy-proof rules. Based on this characterization, we show that most rules considered in Bossert and Sprumont (2014) and Athanasoglou (2016, 2019) are not minimally strategy-proof (while being betweenness strategy-proof). This emphasizes the critical role of linearity when imposed to order extensions. Moreover, we show that a rule is strategy-proof for a rich domain of order extensions if and only if it is either constant or dictatorial, where richness requires that each ordering of a pair of orders can prevail in some hyper-order. We also discuss the existence of rules that are strategy-proof for all order extensions that satisfy the Kemeny distance criterion.
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    The Core of Shapley-Scarf markets with couples
    (Elsevier Science Sa, 2011) Dogan, Onur; Laffond, Gilbert; Laine, Jean
    We extend the Shapley-Scarf model of markets for indivisible goods without money to the case where couples of agents have joint preferences over the set of allocations. We show that the domain of (weakly) lexicographic preferences is maximal (for inclusion) for the existence of Core allocations. This result also holds in the case where the set of agents is partitioned into non-empty coalitions with any size, as well as for the class of markets studied in Konishi et al. (2001), where individuals exchange several types of purely indivisible goods. (C) 2010 Elsevier B.V. All rights reserved.