Lin Meiyan, Ma Lijun, Ying Chengshuo
College of Management and Institute of Big Data, Intelligent Management and Decision, Shenzhen University, Shenzhen, China.
Department of Systems Engineering and Engineering Management and Centre of Systems Informatics Engineering, City University of Hong Kong, Kowloon, Hong Kong.
Transp Res E Logist Transp Rev. 2021 Jan;145:102177. doi: 10.1016/j.tre.2020.102177. Epub 2020 Dec 29.
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.
创新技术(如物联网、大数据分析、区块链、云计算及应用程序)的出现,使得家庭医疗保健(HHC)服务的提供模式从传统机构转向了服务共享平台。在家庭医疗保健环境下,服务共享平台面临的一个主要挑战是,在考虑护理需求和服务提供者异质性的同时,实现供需匹配。从服务共享平台针对三个利益相关者(即平台、护理人员和客户)的集中视角来看,会采用不同的匹配策略,包括“利己”策略、“客户至上”策略、“劳逸结合”策略和“社会福利”策略。在运营层面解决匹配问题时,平台必须遵守各种要求和规则,包括休息要求、时间依赖性和灵活的服务时长。在本研究中,设计了混合整数线性规划模型和分支定价方法,以使用不同的匹配策略实现供需匹配,同时满足所有要求和规则。研究了关键因素对绩效指标(如平台收入、护理人员利润和客户剩余)的影响,并对匹配策略进行了比较。结果表明,“客户至上”策略和“利己”策略从灵活的服务时长中获益更多,然而,与“社会福利”策略和“劳逸结合”策略相比,它们分别受到休息要求和时间依赖性的负面影响更大或更小。“社会福利”策略与其他三种策略的比较表明,前一种策略对服务共享平台的所有三个利益相关者以及政府都有益。服务共享平台与传统家庭医疗保健机构的另一个比较表明,共享经济对护理人员利润和客户剩余有积极影响。