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Matching daily home health-care demands with supply in service-sharing platforms

The availability of innovative technologies (e.g., the Internet of Things, big data analytics, blockchain, the cloud, and applications) has led to a shift in the provision of home health-care (HHC) services from traditional institutions to service-sharing platforms. In the HHC context, one main chal...

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Detalles Bibliográficos
Autores principales: Lin, Meiyan, Ma, Lijun, Ying, Chengshuo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7769751/
https://www.ncbi.nlm.nih.gov/pubmed/33390765
http://dx.doi.org/10.1016/j.tre.2020.102177
Descripción
Sumario:The availability of innovative technologies (e.g., the Internet of Things, big data analytics, blockchain, the cloud, and applications) has led to a shift in the provision of home health-care (HHC) services from traditional institutions to service-sharing platforms. In the HHC context, one main challenge faced by service-sharing platforms is the matching of demand with supply, while considering the heterogeneity of care requests and service providers. From a centralized perspective of service-sharing platforms regarding three stakeholders (i.e., platform, caregiver, and customer), different matching strategies are used, including the “self-interested”, “customer-first”, “hard-work-happy-life”, and “social-welfare” strategies. When addressing the matching problem at an operational level, the platforms must comply with various requirements and rules, including break requirements, temporal dependencies, and flexible service durations. In this study, mixed-integer linear programming models and a branch-and-price approach are designed to match demand with supply using different matching strategies while satisfying all of the requirements and rules. The effects of key factors on performance indicators (e.g., platform revenue, caregiver profit, and customer surplus) are examined, and the matching strategies are compared. The results indicate that the “customer-first” and “self-interested” strategies benefit more from flexible service durations, however they are more and less negatively affected by break requirements and temporal dependencies, respectively, as compared to the “social-welfare” and “hard-work-happy-life” strategies. A comparison between the “social-welfare” strategy and the other three strategies indicates that the former strategy is beneficial for all three stakeholders of the service-sharing platforms as well as the government. Another comparison between the service-sharing platforms and traditional HHC institutions indicates the sharing economy has a positive impact on caregiver profit and customer surplus.