{"title":"Capacity decisions and revenue sharing in a telemedicine healthcare system","authors":"Liangliang Sun, Miao Yu, Fenghao Wang","doi":"10.1007/s10878-023-01095-6","DOIUrl":null,"url":null,"abstract":"<p>This paper studies the operations of a telemedicine service system consisting of independent hospitals [general hospital (GH) and telemedicine firm (TF)]. Through the healthcare alliance, the GH and the TF collaborate in capacity decisions and revenue sharing, and establish a green channel to refer patients. We adopt a two-stage game model to study a revenue sharing scheme of the telemedicine healthcare alliance. In the first-stage the game, the GH and the TF negotiate a revenue-sharing ratio to distribute the revenue of the referred patients. In the second stage game, given the profit-sharing ratio, GH makes capacity allocation decisions, and TF determines its own price to maximize its own revenue. Results show that the revenue sharing scheme can increase profits and promote collaboration between GH and TF. When a large number of mild patients arrive at the GH, the GH tends to participate in the alliance. For the TF, high prices do not always yield high profit under the comprehensive influence of the alliance.</p>","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":null,"pages":null},"PeriodicalIF":0.9000,"publicationDate":"2023-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Combinatorial Optimization","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1007/s10878-023-01095-6","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
This paper studies the operations of a telemedicine service system consisting of independent hospitals [general hospital (GH) and telemedicine firm (TF)]. Through the healthcare alliance, the GH and the TF collaborate in capacity decisions and revenue sharing, and establish a green channel to refer patients. We adopt a two-stage game model to study a revenue sharing scheme of the telemedicine healthcare alliance. In the first-stage the game, the GH and the TF negotiate a revenue-sharing ratio to distribute the revenue of the referred patients. In the second stage game, given the profit-sharing ratio, GH makes capacity allocation decisions, and TF determines its own price to maximize its own revenue. Results show that the revenue sharing scheme can increase profits and promote collaboration between GH and TF. When a large number of mild patients arrive at the GH, the GH tends to participate in the alliance. For the TF, high prices do not always yield high profit under the comprehensive influence of the alliance.
期刊介绍:
The objective of Journal of Combinatorial Optimization is to advance and promote the theory and applications of combinatorial optimization, which is an area of research at the intersection of applied mathematics, computer science, and operations research and which overlaps with many other areas such as computation complexity, computational biology, VLSI design, communication networks, and management science. It includes complexity analysis and algorithm design for combinatorial optimization problems, numerical experiments and problem discovery with applications in science and engineering.
The Journal of Combinatorial Optimization publishes refereed papers dealing with all theoretical, computational and applied aspects of combinatorial optimization. It also publishes reviews of appropriate books and special issues of journals.