The revealed preference theory of stable matchings with one-sided preferences

Hu, Gaoji; Li, Jiangtao; Tang, Rui

doi:10.1016/j.geb.2020.08.015

Cited by 7 publications

(3 citation statements)

References 11 publications

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“…The spatial difference of the matching subjects has a certain impact in the matching process [30]. The common of two parties in the matching market could obtain an equilibrium solution [31]. The preference of one side is also a kind of matching problem [32].…”

Section: Two-sided Matchingmentioning

confidence: 99%

Selecting Suitable Key Supplier for Core Components During Smart Complex Equipment Central-Private Enterprises Collaborative Development Process: From Two Different Forms of Evaluation Information and Matching Perspective

Huang,

Qi,

Chen

et al. 2023

J. of Syst. Eng. Electron.

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With the development of central-private enterprises integration, selecting suitable key suppliers are able to provide core components for smart complex equipment. We consider selecting suitable key suppliers from matching perspective, for it not only satisfies natural development of smart complex equipment, it is also a good implementation of equipment project in central-private enterprises integration context. In in this paper, we carry out two parts of research, one is evaluation attributes based on comprehensive analysis, and the other is matching process between key suppliers and core components based on the matching attribute. In practical analysis process, we employ comprehensive evaluated analysis methods to acquire relevant attributes for the matching process that follows. In the analysis process, we adopt entropy-maximum deviation method (MDM)decision-making trial and evaluation laboratory (DEMATEL)-technique for order preference by similarity to an ideal solution (TOP-SIS) to obtain a comprehensive analysis. The entropy-MDM is applied to get weight value, DEMATEL is utilized to obtain internal relations, and TOPSIS is adopted to get ideal evaluated solution. We consider aggregating two types of evaluation information according to similarities of smart complex equipment based on the combination between geometric mean and arithmetic mean. Moreover, based on the aforementioned attributes and generalized power Heronian mean operator, we aggregate preference information to acquire relevant satisfaction degree, then combine the constructed matching model to get suitable key supplier. Through comprehensive analysis of selecting suitable suppliers, we know that two-sided matching and information aggregation can provide more research perspectives for smart complex equipment. Through analysis for relevant factors, we find that leading role and service level are also significant for the smart complex equipment development process.

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Section: Two-sided Matchingmentioning

confidence: 99%

Selecting Suitable Key Supplier for Core Components During Smart Complex Equipment Central-Private Enterprises Collaborative Development Process: From Two Different Forms of Evaluation Information and Matching Perspective

Huang,

Qi,

Chen

et al. 2023

J. of Syst. Eng. Electron.

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“…Pittel [8] proposed a TSM model under strict preference order. Hu et al [9] presented a stable TSM model with oneside preference. Antler [10] studied TSMDM problems based on the endogenous preference ordinal number and proposed a new TSMDM method.…”

Section: Introductionmentioning

confidence: 99%

Two-Sided Stable Matching Decision-Making Method Considering Matching Intention under a Hesitant Fuzzy Environment

Yue¹,

Deng²

2023

Computer Modeling in Engineering &Amp; Sciences

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In this paper, a stable two-sided matching (TSM) method considering the matching intention of agents under a hesitant fuzzy environment is proposed. The method uses a hesitant fuzzy element (HFE) as its basis. First, the HFE preference matrix is transformed into the normalized HFE preference matrix. On this basis, the distance and the projection of the normalized HFEs on positive and negative ideal solutions are calculated. Then, the normalized HFEs are transformed into agent satisfactions. Considering the stable matching constraints, a multiobjective programming model with the objective of maximizing the satisfactions of two-sided agents is constructed. Based on the agent satisfaction matrix, the matching intention matrix of two-sided agents is built. According to the agent satisfaction matrix and matching intention matrix, the comprehensive satisfaction matrix is set up. Furthermore, the multiobjective programming model based on satisfactions is transformed into a multiobjective programming model based on comprehensive satisfactions. Using the G-S algorithm, the multiobjective programming model based on comprehensive satisfactions is solved, and then the best TSM scheme is obtained. Finally, a terminal distribution example is used to verify the feasibility and effectiveness of the proposed method.

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“…11 See also Echenique (2008), Cherchye, Demuynck, De Rock, and Vermeulen (2017), and Hu, Li, and Tang (2020) for other revealed preference approaches to matching models. …”

mentioning

confidence: 99%

On the revealed preference analysis of stable aggregate matchings

Demuynck

Salman

2022

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Echenique, Lee, Shum, and Yenmez (2013) established the testable revealed preference restrictions for stable aggregate matching with transferable and nontransferable utility and for extremal stable matchings. In this paper, we rephrase their restrictions in terms of properties on a corresponding bipartite graph. From this, we obtain a simple condition that verifies whether a given aggregate matching is rationalizable. For matchings that are not rationalizable, we provide a simple greedy algorithm that computes the minimum number of matches that need to be removed to obtain a rationalizable matching. We also show that the related problem of finding the minimum number of types that we need to remove in order to obtain a rationalizable matching is NP‐complete.

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The revealed preference theory of stable matchings with one-sided preferences

Cited by 7 publications

References 11 publications

Selecting Suitable Key Supplier for Core Components During Smart Complex Equipment Central-Private Enterprises Collaborative Development Process: From Two Different Forms of Evaluation Information and Matching Perspective

Selecting Suitable Key Supplier for Core Components During Smart Complex Equipment Central-Private Enterprises Collaborative Development Process: From Two Different Forms of Evaluation Information and Matching Perspective

Two-Sided Stable Matching Decision-Making Method Considering Matching Intention under a Hesitant Fuzzy Environment

On the revealed preference analysis of stable aggregate matchings

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