Efficient allocation with ordinal preference intensities

[2011.04306] Efficient allocation with ordinal preference intensities Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Economics > Theoretical Economics arXiv:2011.04306 (econ) [Submitted on 9 Nov 2020 ( v1 ), last revised 20 Jul 2026 (this version, v9)] Title: Efficient allocation with ordinal preference intensities Authors: Georgios Gerasimou View a PDF of the paper titled Efficient allocation with ordinal preference intensities, by Georgios Gerasimou View PDF HTML (experimental) Abstract: Standard allocation methods that rely on ordinal preferences ignore how strongly agents value different improvements. On the other hand, methods based on cardinal utilities require assumptions that are often considered too demanding. This paper studies the classic one-to-one assignment problem in the middle-ground environment of *ordinal* preference intensities: agents rank alternatives as well as preference improvements, without necessarily being able to quantify these comparisons. The paper introduces an interpersonal comparability assumption for this novel social-choice analytical setting. Building on it, it proposes and analyses the *intensity-efficiency* criterion. This refines Pareto's criterion by discarding any allocation that is worse than another according to an intuitive intensity-dominance relation. The feasibility and applicability of this framework in matching problems is illustrated with two quadratic-time algorithms which, respectively, elicit ordinal intensity rankings and extend the classic Random Priority mechanism in a welfare-improving direction. Subjects: Theoretical Economics (econ.TH) Cite as: arXiv:2011.04306 [econ.TH] (or arXiv:2011.04306v9 [econ.TH] for this version) https://doi.org/10.48550/arXiv.2011.04306 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Georgios Gerasimou [ view email ] [v1] Mon, 9 Nov 2020 10:23:22 UTC (9 KB) [v2] Wed, 31 Jan 2024 17:23:49 UTC (16 KB) [v3] Mon, 30 Dec 2024 13:41:26 UTC (28 KB) [v4] Wed, 22 Jan 2025 18:50:47 UTC (28 KB) [v5] Wed, 27 Aug 2025 17:19:19 UTC (48 KB) [v6] Sun, 1 Mar 2026 11:33:32 UTC (56 KB) [v7] Fri, 27 Mar 2026 19:01:07 UTC (57 KB) [v8] Tue, 14 Apr 2026 18:58:33 UTC (44 KB) [v9] Mon, 20 Jul 2026 17:26:13 UTC (61 KB) Full-text links: Access Paper: View a PDF of the paper titled Efficient allocation with ordinal preference intensities, by Georgios Gerasimou View PDF HTML (experimental) TeX Source view license Current browse context: econ.TH < prev | next > new | recent | 2020-11 Change to browse by: econ References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab) Major funding support from

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