Dynamic Matching Market Design

Akbarpour, Mohammad; Li, Shengwu; Gharan, Shayan Oveis

doi:10.2139/ssrn.2394319

Cited by 28 publications

(50 citation statements)

References 23 publications

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“…Pricing is assumed to be highly dynamic for the considerations reviewed in the previous section, hence the price of a randomly selected seller is considered to be a random variable Y associated with a probability distribution function f * (y). 2 This assumption is commonly used in eCommerce research [85,185,176] and is also supported by empirical research in well-established online markets [24,23,33,40].…”

Section: Modelmentioning

confidence: 86%

“…of the population -have kidney disease. 2 For many, kidney disease will progress to outright kidney failure and with it, the need for a kidney transplant. Transplant organs can be sourced from cadavers or willing living donors.…”

Section: List Of Tablesmentioning

confidence: 99%

“…In 2005, Roth et al [152] suggested a mechanism that considers only pairwise exchanges based on the surgical infrastructure that was available at that time. The topic has attracted researchers from non-medical fields such as economics [150,151,2] and computer science [1,29,44,46,47,48,5,105,101]. The National Organ Transplant Act of 1984 makes it illegal to buy or sell a kidney in the US, thus making donation the only viable option for kidney transplantation [147,99].…”

Section: Kidney Exchangementioning

confidence: 99%

“…Since there is need for a considerable amount of prices for the "despair" phase, the top half of prices known to the CSA (sp 7 − sp 12 ) is reserved for that phase, and the bottom half of prices (sp 1 − sp 6 ) is divided equally between the "anchor" and the "effort" phases. 2 In addition, the prices of "effort" are divided into two subsets of prices, effortMid and effortMin, where effortMid is twice the size of effortMin. Therefore, the algorithm divides lower subset of prices into two equal parts (Steps 2-5).…”

mentioning

confidence: 99%

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Intelligent Mechanisms for Platforms in Modern Markets

Hajaj¹

2019

Preprint

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This thesis explores the use of autonomous agents serving as mediators between different entities in modern markets to maximize an expected revenue (e.g., the agents' own profit or users' social welfare). This mediation can take many forms and serve many purposes, such as buyers and sellers at online shopping environments, men and women at dating sites, and different traders at barter markets. These agents differ from one another in terms such as the cost of their mediation services (e.g, they can offer their services for a fee or complimentary). In the first case, when the services are costly, agents must ponder the terms they set for their services. Similarly, when offering their services for free they have to be as appealing as possible in order to overcome external competition. This thesis provides theoretically-justified and empirically-validated approaches for designing and operating intelligent mechanisms for mediation agents in both electronic and barter markets. While two of the mechanisms presented within this thesis guide the platform for how to use selective information disclosure for its benefit, a different one is designed specifically in order to avoid selective information disclosure to the platform. The research is based on both theoretical analysis and online validation of suggested heuristics. Theoretical analysis is carried out using concepts from search theory, and game theory and the online validation is based on Amazon Mechanical Turk, a well-known crowdsourcing platform imitating people's behavior in real-life.The models used in this thesis consider settings of autonomous, fully-rational, and self-interested agents interacting with both fully-rational agents and bounded-rational people, and how the difference in their decision-making processes may imply differently, yet correlated, strategies for the system designer. The different model variants are applicable and can be mapped onto various different real-life applications (e.g., online shopping, car purchasing, and barter markets). The models differ primarily in the assumptions they make. In electronic markets, assumptions relating to the agents' source of income and the users' computational capabilities (fully-rational agents vs. bounded-rational people). For barter markets, this thesis focuses on fully-rational agents that differ in the number of goods they hold and can be traded on the market. Based on the common model for these markets, this thesis provides a proof of impossibility result on the ability to enforce the agents' strategy-proof behavior regardless of the means used. Still, the thesis shows that by adding a set of real-life assumptions on the model, one can circumvent this impossibility result and validate that the truthful strategy is indeed the dominant one. The analysis is accompanied by extensive simulations and online experiments, making use of various testbeds. The simulations and online experiments are used to validate the applicability of the suggested mechanisms for modern markets and to the different entities populating them.

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Section: Modelmentioning

confidence: 86%

Section: List Of Tablesmentioning

confidence: 99%

Section: Kidney Exchangementioning

confidence: 99%

mentioning

confidence: 99%

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Intelligent Mechanisms for Platforms in Modern Markets

Hajaj¹

2019

Preprint

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“…Recent work has addressed this added form of dynamism from a theoretical [Ünver 2010; Akbarpour et al 2014;Anderson et al 2015a] and experimental [Awasthi and Sandholm 2009;Dickerson et al 2012a;Dickerson and Sandholm 2015] point of view. Theoretical models have not addressed the case where an edge in the current graph may not exist (as we do in this paper); the more recent experimental papers have incorporated this possibility, but have not considered the problem of querying edges before recommending a final matching.…”

Section: Kidney Exchangementioning

confidence: 99%

Ignorance is Almost Bliss

Blum¹,

Dickerson²,

Haghtalab³

et al. 2015

Proceedings of the Sixteenth ACM Conference on Economics and Computation

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The stochastic matching problem deals with finding a maximum matching in a graph whose edges are unknown but can be accessed via queries. This is a special case of stochastic k-set packing, where the problem is to find a maximum packing of sets, each of which exists with some probability. In this paper, we provide edge and set query algorithms for these two problems, respectively, that provably achieve some fraction of the omniscient optimal solution.Our main theoretical result for the stochastic matching (i.e., 2-set packing) problem is the design of an adaptive algorithm that queries only a constant number of edges per vertex and achieves a (1 − ) fraction of the omniscient optimal solution, for an arbitrarily small > 0. Moreover, this adaptive algorithm performs the queries in only a constant number of rounds. We complement this result with a non-adaptive (i.e., one round of queries) algorithm that achieves a (0.5 − ) fraction of the omniscient optimum. We also extend both our results to stochastic k-set packing by designing an adaptive algorithm that achieves a ( 2 k − ) fraction of the omniscient optimal solution, again with only O(1) queries per element. This guarantee is close to the best known polynomial-time approximation ratio of 3 k+1 − for the deterministic k-set packing problem [Fürer and Yu 2013].We empirically explore the application of (adaptations of) these algorithms to the kidney exchange problem, where patients with end-stage renal failure swap willing but incompatible donors. We show on both generated data and on real data from the first 169 match runs of the UNOS nationwide kidney exchange that even a very small number of non-adaptive edge queries per vertex results in large gains in expected successful matches.

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Market Design

Ashlagi

2018

Handbook of Healthcare Analytics

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Dynamic Matching Market Design

Cited by 28 publications

References 23 publications

Intelligent Mechanisms for Platforms in Modern Markets

Intelligent Mechanisms for Platforms in Modern Markets

Ignorance is Almost Bliss

Market Design

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