Abstract
The aim of this paper was to introduce a new method to healthcare markets and analyze the value difference of different market segments. Data clustering is an important data mining technology in engineering and technology. Ant colony optimization algorithm, which is an emerging bionics evolutionary algorithm, has strong robustness and adaptability. Clustering method based on ant colony algorithm has been widely applied in many fields. Market segmentation is the basis of hospitals’ market understanding and service management strategy making. This paper classified healthcare customers into three groups based on ant colony clustering algorithm. The experimental results validate the algorithm’s efficiency in healthcare market segmentation. This paper also provide data basis for Chinese hospitals to further improve the efficiency and effectiveness of healthcare services.
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Jiang, Q.W., Wang, J. (2011). Applied Research of Ant Colony Clustering Algorithms in Healthcare Consumer Segments. In: Zhou, M. (eds) Education and Management. ISAEBD 2011. Communications in Computer and Information Science, vol 210. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23065-3_49
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DOI: https://doi.org/10.1007/978-3-642-23065-3_49
Publisher Name: Springer, Berlin, Heidelberg
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