Open Access
ARTICLE
An Adaptive Parameter-Free Optimal Number of Market Segments Estimation Algorithm Based on a New Internal Validity Index
Jianfang Qi1, Yue Li1,3, Haibin Jin1, Jianying Feng1, Dong Tian1, Weisong Mu1,2,*
1
College of Information and Electrical Engineering, China Agricultural University, Beijing, 100083, China
2
Key Laboratory of Viticulture and Enology, Ministry of Agriculture, Beijing, 100083, China
3
Institute of Population Research, Peking University, Beijing, 100871, China
* Corresponding Author: Weisong Mu. Email:
Computer Modeling in Engineering & Sciences 2023, 137(1), 197-232. https://doi.org/10.32604/cmes.2023.026113
Received 16 August 2022; Accepted 16 December 2022; Issue published 23 April 2023
Abstract
An appropriate optimal number of market segments (ONS) estimation is essential for an enterprise to achieve
successful market segmentation, but at present, there is a serious lack of attention to this issue in market segmentation. In our study, an independent adaptive ONS estimation method BWCON-NSDK-means++ is proposed by
integrating a new internal validity index (IVI) Between-Within-Connectivity (BWCON) and a new stable clustering
algorithm Natural-SDK-means++ (NSDK-means++) in a novel way. First, to complete the evaluation dimensions
of the existing IVIs, we designed a connectivity formula based on the neighbor relationship and proposed the
BWCON by integrating the connectivity with other two commonly considered measures of compactness and
separation. Then, considering the stability, number of parameters and clustering performance, we proposed the
NSDK-means++to participate in the integration where the natural neighbor was used to optimize the initial cluster
centers (ICCs) determination strategy in the SDK-means++. At last, to ensure the objectivity of the estimated ONS,
we designed a BWCON-based ONS estimation framework that does not require the user to set any parameters
in advance and integrated the NSDK-means++ into this framework forming a practical ONS estimation tool
BWCON-NSDK-means++. The final experimental results show that the proposed BWCON and NSDK-means++
are significantly more suitable than their respective existing models to participate in the integration for determining
the ONS, and the proposed BWCON-NSDK-means++ is demonstrably superior to the BWCON-KMA, BWCONMBK, BWCON-KM++, BWCON-RKM++, BWCON-SDKM++, BWCON-Single linkage, BWCON-Complete
linkage, BWCON-Average linkage and BWCON-Ward linkage in terms of the ONS estimation. Moreover, as an
independent market segmentation tool, the BWCON-NSDK-means++ also outperforms the existing models with
respect to the inter-market differentiation and sub-market size.
Keywords
Cite This Article
APA Style
Qi, J., Li, Y., Jin, H., Feng, J., Tian, D. et al. (2023). An adaptive parameter-free optimal number of market segments estimation algorithm based on a new internal validity index. Computer Modeling in Engineering & Sciences, 137(1), 197-232. https://doi.org/10.32604/cmes.2023.026113
Vancouver Style
Qi J, Li Y, Jin H, Feng J, Tian D, Mu W. An adaptive parameter-free optimal number of market segments estimation algorithm based on a new internal validity index. Comput Model Eng Sci. 2023;137(1):197-232 https://doi.org/10.32604/cmes.2023.026113
IEEE Style
J. Qi, Y. Li, H. Jin, J. Feng, D. Tian, and W. Mu "An Adaptive Parameter-Free Optimal Number of Market Segments Estimation Algorithm Based on a New Internal Validity Index," Comput. Model. Eng. Sci., vol. 137, no. 1, pp. 197-232. 2023. https://doi.org/10.32604/cmes.2023.026113