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dc.contributor.authorKumar Singh, Vikash
dc.contributor.authorMukhopadhyay, Sajal
dc.contributor.authorXhafa Xhafa, Fatos
dc.contributor.authorSharma, Aniruddh
dc.contributor.authorRoy, Arpan
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Ciències de la Computació
dc.date.accessioned2018-11-22T13:27:46Z
dc.date.available2018-11-22T13:27:46Z
dc.date.issued2018-11
dc.identifier.citationKumar, V., Mukhopadhyay, S., Xhafa, F., Sharma, A., Roy, A. Hiring expert consultants in e-healthcare: an analytics-based two sided matching approach. "Transactions on computational collective intelligence", Novembre 2018, vol. 30, p. 178-199.
dc.identifier.issn2190-9288
dc.identifier.urihttp://hdl.handle.net/2117/124934
dc.description.abstractVery often in some censorious healthcare scenario, there may be a need to have some expert consultancies (especially by doctors) that are not available in-house to the hospitals. Earlier, this interesting healthcare scenario of hiring the expert consultants (mainly doctors) from outside of the hospitals had been studied with the robust concepts of mechanism design with money and mechanism design without money. In this paper, we explore the more realistic two sided matching market in our healthcare set-up. In this, the members of the two participating communities, namely the patients and the doctors are revealing the strict preference ordering over the members of the opposite community for a stipulated amount of time. We assume that the patients and doctors are strategic in nature. With the theoretical analysis, we demonstrate that the TOMHECs, that results in the stable allocation of doctors to the patients, satisfies the several economic properties such as strategy-proof-ness (or truthfulness) and optimality. Further, the analytically based analysis of our proposed mechanisms i.e. RAMHECs and TOMHECs are carried out on the ground of the expected distance of the allocation done by the mechanisms from the top most preference. The proposed mechanisms are also validated with the help of exhaustive experiments.
dc.format.extent22 p.
dc.language.isoeng
dc.subjectÀrees temàtiques de la UPC::Informàtica
dc.subject.lcshGame theory
dc.subject.lcshSwarm intelligence
dc.subject.otherE-healthcare
dc.subject.otherAnalytics
dc.subject.otherCollective intelligence
dc.subject.otherHiring
dc.subject.otherMechanism design
dc.subject.otherStable allocation
dc.titleHiring expert consultants in e-healthcare: an analytics-based two sided matching approach
dc.typeArticle
dc.subject.lemacJocs, Teoria de
dc.subject.lemacIntel·ligència col·lectiva
dc.subject.lemacTelemedicina
dc.identifier.doi10.1007/978-3-319-99810-7_9
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://link.springer.com/chapter/10.1007%2F978-3-319-99810-7_9
dc.rights.accessOpen Access
local.identifier.drac23507442
dc.description.versionPostprint (author's final draft)
local.citation.authorKumar, V.; Mukhopadhyay, S.; Xhafa, F.; Sharma, A.; Roy, A.
local.citation.publicationNameTransactions on computational collective intelligence
local.citation.volume30
local.citation.startingPage178
local.citation.endingPage199


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