Segmentation approaches in data-mining: A comparison of RFM, CHAID, and logistic regression

McCarty, John A.; Hastak, Manoj

doi:10.1016/j.jbusres.2006.06.015

Cited by 250 publications

(138 citation statements)

References 9 publications

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“…It attempts to predict values of the dependent variable from a number of predictor variables (McCarty & Hastak, 2007). The CHAID algorithm is a stepwise progression (Kass, 1980).…”

Section: Discussionmentioning

confidence: 99%

New Constructs for the Prediction of Self-Initiated International Mobility: An Exploratory Study

Thorn

Inkson

Carr

2013

Journal of Pacific Rim Psychology

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T his study aims to explore relationships between the motives for international mobility and observed mobility patterns. The key motives of 2,608 skilled expatriate New Zealanders were identified as cultural and travel opportunities, career, economics, affiliations, political environment, and quality-oflife. Mobility patterns, described here as the frequency, duration and cessation of mobility and the nature of the destination in terms of development level and cultural distance, were investigated. Desire for cultural and travel opportunities was the dominant motive, and the best predictor of cessation of mobility and development level of the destination. Career motives predicted duration of mobility and cultural difference of the destination. Linking motivation and actual mobility is a novel contribution to the theorisation of self-initiated mobility. Countries and organisations that understand this linkage may ultimately gain competitive advantage.

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“…It attempts to predict values of the dependent variable from a number of predictor variables (McCarty & Hastak, 2007). The CHAID algorithm is a stepwise progression (Kass, 1980).…”

Section: Discussionmentioning

confidence: 99%

New Constructs for the Prediction of Self-Initiated International Mobility: An Exploratory Study

Thorn

Inkson

Carr

2013

Journal of Pacific Rim Psychology

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“…The procedure continued until no other splits were significant. [20] 2.5 Evaluation index RIV was used to measure the reduction in variation in the dependent variable achieved by the classification, which re-flected DRGs' predictive validity. High RIV predicted a rigorous classification system.…”

Section: Methodsmentioning

confidence: 99%

Developing case-mix standards with the Diagnosis-related Groups for payment reforms and hospital management in China: A case study in Xiamen city

Zeng

Lin

et al. 2016

IJH

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Objective: To inform health insurance payment reforms and hospital cost management by investigating the case-mix of viral hepatitis, a common disease, in a Chinese city. Methods: All inpatient medical records of viral hepatitis of selected hospitals in Xiamen from 2008 to 2013 were collected. Both univariate and multivariate analyses were performed to test the association between hospitalization costs and other key variables. The CHAID model was employed to generate the Diagnosis-related Groups (DRGS). Evaluation indexes were adopted to evaluate the grouped results. Standard expenditures were estimated for each group. Results: Gender, age, marital status, mode of payment, admission condition, discharged condition and length of stay were found significantly associated with inpatient expenditures, with p values smaller than .001. Eleven diagnosis-related groups were obtained with the CHAID methods and three classification nodes were obtained from the CHAID decision tree, including age, admission status and mode of payment. The analysis revealed a considerable discrepancy in expenditures across groups with similar characteristics. This variance suggests the existence of inflated inpatient costs as well as inefficient use of medical resources. Conclusions: The analysis provided more accurate estimation on case-mix costs for a major disease in China. The standard expenditures are of reference values for the social insurance administration in calibrating reimbursement rates in its move to case-mix payment system and helpful for hospital cost management.

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“…At the strategic level, segmentation permits profitable customers identification, market decisions stability (considering the various market segments), and product and service delivery (placing them in the market). At the operational level, segmentation drives organizations to emphasize more on enhanced customer understanding and relationship development (McCarty and Hastak, 2007). In Swift (2001), CRM implementation can benefit the organization in several ways including reduced cost, market value stability, high customer profitability, and, increased customer retention and loyalty.…”

Section: Related Workmentioning

confidence: 99%

Unsupervised Learning Framework for Customer Requisition and Behavioral Pattern Classification

Inyang¹,

Obot²,

Ekpenyong³

et al. 2017

MAS

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Maintaining healthy organization-customers relationship has positive influence on customers' behavioral tendencies as regards preference to products and services, buying behavior, loyalty, satisfaction, and so on. To achieve this, an in-depth analysis of customers' characteristics and purchasing behavioral trend is required. This paper proposes a hybrid unsupervised learning framework consisting of k-means algorithm and self-organizing maps (SOMs) for customer segmentation and behavior analysis. K-means algorithm was used to partition the entire input space of customers' transaction dataset into 3 and 4 disjoint segments based on customers' frequency (F) and monetary value (MV). SOM provided visualization of the underlying clusters and discovered customers' relationships in the dataset. Interaction of F and MV clusters resulted in 12 sub-clusters. An in-depth analysis of each sub-cluster was also performed and appropriate customer relationship management (CRM) strategies established for each sub-cluster. Discovered knowledge will guide effective allocation of resources to each customer cluster and other organizational decision support functions much required by CRM systems.

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Segmentation approaches in data-mining: A comparison of RFM, CHAID, and logistic regression

Cited by 250 publications

References 9 publications

New Constructs for the Prediction of Self-Initiated International Mobility: An Exploratory Study

New Constructs for the Prediction of Self-Initiated International Mobility: An Exploratory Study

Developing case-mix standards with the Diagnosis-related Groups for payment reforms and hospital management in China: A case study in Xiamen city

Unsupervised Learning Framework for Customer Requisition and Behavioral Pattern Classification

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