Abstract
The neighborhood rough set theory was adopted for attributes reduction and the weight distribution of condition attributes based on the concept of importance level. Smart elderly care coverage rate is low in China. A decisive role in the adoption of smart elderly care is still a problem that needs to be addressed. This study contributes to the adoption of smart elderly care was selected as the decision attribute. The remaining attributes are used as conditional attributes and the multi-level symmetric attribute set for assessing acceptance of smart elderly care. Prior studies are not included smart elderly care adoption attributes in multi-levels; hence, this problem needs to be addressed. The results of this study indicate that the condition attribute of gender has the greatest influence on the decision attribute. The condition attribute of living expenses for smart elderly care has the second largest impact on decision attribute. Children’s support for the elderly decency of the novel elderly care system and the acceptance of non-traditional elderly care methods belong to the primary condition attribute of traditional concept. The result indicates traditional concepts have a certain impact on the adoption of smart elderly care and a condition attribute of residence also has a slight influence on the symmetric decision attribute. The sensitivity analysis shows the insights for uncertainties and provides as a basis for the analysis of the attributes in the smart elderly care service adoption.
Highlights
The neighborhood rough set theory after the overlapping attributes are deleted, and the degree of influence of the attributes on the adoption behavior of smart elderly care is analyzed
The attributes take and adopt smart elderly care service taken as the decision attribute, and the rest are conditional attributes
The results provide a valuable reference for the future development of smart elderly care services
Summary
The neighborhood rough set theory after the overlapping attributes are deleted, and the degree of influence of the attributes on the adoption behavior of smart elderly care is analyzed. Symmetry 2020, 12, 297 consumer-centric firms satisfy consumer needs and make changes to avoid blindness of firm decisions to improve firm services and competitiveness with consumer data through rough sets [1]. One of usable application of Rough set theory is the processing of discrete data. This study is necessary to discretize the data when processes continuous data. The drawback of this application is a large amount of information loss, and the discrete data cannot accurately reflect the classification of information [2]
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