Abstract: With the deepening of the digital economy, data has become a factor of production and plays an important role. Nowadays, population aging brings new challenges to the construction of senior care service resources. Combining advanced technology to realize data-driven senior care services has attracted the extensive attention of the fields of sociology, public administration, and data science. For the assessment of resource allocation for the construction of senior care services, most of the existing studies have considered the situation in which the assessment indicators are independent of each other. The weights and interaction coefficients of the indicators are usually based on the preferences of decision makers, which is inconsistent. One challenge is to determine the weights of interdependent criteria based only on a given set of objective data without the subjective judgment of decision makers. While traditional perspectives focus more on collecting, cleaning, and analyzing data to extract valuable information, data element perspective starts with objective data. It identifies relevant data elements, establishes relationships between data elements, and provides insights into the connotations of data elements.
In view of this, to reduce the influence of decision-makers’subjective factor judgments, this study proposes a multi-indicator evaluation method for senior care service resources construction and allocation schemes. The method is based on the data element perspective and uses data-driven livelihood service thinking. It integrates the respective characteristics of fuzzy, Shapley value and Marichal entropy. The method addresses the demand characteristics of senior care services and constructs the evaluation index system from the three dimensions of daily care, medical care, and spiritual comfort respectively. It then determines the objective weights of the indexes and uses the optimization model to objectively obtain the interaction coefficients, weights, and program satisfactions of the criteria on the multi-level structure. This approach effectively avoids the influence of inconsistent subjective preferences. It can accurately reflect the complexity of objective senior care service resources construction and can also more accurately reflect the interrelationship between different variables in the system. According to the change of fuzzy measure, it can reflect the existence of the mutual influence relationship between different evaluation indexes of senior care service resources. By using this feature of fuzzy measure, it can better analyze the change of each index in the evaluation indexes of the senior care service resources construction program. Compared with traditional evaluation methods for all kinds of senior care services, the method proposed in this paper realizes the use of objective data and objective weights. It ensures that the evaluation results are not affected by the inconsistency or uncertainty of subjective judgments. The proposed method effectively avoids interdependent interactions in the evaluation indexes and weights interfered with by subjective factors and can more objectively respond to the evaluation program. In addition, data on the construction of senior care service resources in 16 administrative districts of Shanghai are selected for empirical analysis to further verify the feasibility and effectiveness of the proposed method.
According to the experimental results, the following conclusions can be drawn: 1)The quantitative analysis of elderly service resource data based on the constructed objective weighting model method presents to a certain extent the interplay between various types of senior care service resources. The interactions between all the sub-indicators are positive. 2)Fuzzy measurements react to the assessment of different senior care service resources construction program evaluation indexes. There is a cross-influence phenomenon between the variables, and their values affect the overall performance of the overall senior care service resources construction evaluation system. The weight of spiritual comfort is the largest in the evaluation of senior care service resources construction allocation, followed by medical care, and finally daily care. 3)The evaluation method of the senior care service resources construction allocation program constructed in this paper is feasible and effective. The results of this study are useful for the government in promoting the construction of senior care service resources. It can help scientifically and reasonably utilize resources and improve the level of service.
The findings of this paper are of guiding significance for the construction of senior care service resources in data-driven livelihood. However, there is still room for further optimization. In practice, due to the different characteristics of the structure of the elderly population, economic conditions, and assessment mechanisms of the relevant departments in various places, the original impetus in the implementation of the construction in various places is different. This leads to different evaluation results. The follow-up research work will consider an in-depth advancement for these characteristics of the factors.

Key words: data Elements, senior care service, multi-indicator evaluation, objective weights, decision support

摘要： 数据作为当前社会生产各领域中重要的资源,尤其在智慧民生服务中发挥越来越重要的作用。基于数据要素驱动民生服务视角,如何客观对民生服务中养老服务资源实施建设方案科学评价,这对完善整个养老服务体系的建设显得尤为重要。本文从数据要素驱动智慧民生的角度出发,结合模糊理论、博弈论及信息熵相关知识,提出一种多指标的养老服务资源建设分配方案评价方法。该方法针对养老服务的需求特征,分别从日常照料、医疗护理和精神慰藉三个维度构建评价指标体系,进而确定指标的客观权重,并利用优化模型客观地获得多层次结构上标准的交互系数、权重和方案满意度,有效避免了主观偏好不一致的影响。同时,以上海市16个行政区养老服务资源建设分配方案进行方法验证实验。实验结果显示,本文构建的养老服务资源分配方案评估方法具有可行性,且与实际情况契合。本研究是数据驱动民生服务的具体实践,其研究结果可为政府养老服务资源的合理建设实施提供一定的辅助科学决策支持,也为数据要素在智慧民生中提升建设与管理水平提供可借鉴的应用案例。

关键词: 数据要素, 养老服务, 多指标目标评价, 客观权重, 决策支持