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2024 | OriginalPaper | Buchkapitel

Analysis of Data Clustering: Factors Influencing the Demarketing of Breast Milk Alternatives

verfasst von : Samer Yaghi, Samir Baidoun, Mohammed Salem

Erschienen in: AI and Business, and Innovation Research: Understanding the Potential and Risks of AI for Modern Enterprises

Verlag: Springer Nature Switzerland

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Abstract

This study employs data clustering techniques to examine the factors influencing the demarketing of breast milk alternatives. The dataset is subjected to the data clustering approach in order to cluster its variables according to how similar they are. An empirical study using 376 questionnaires from Palestinian breastfeeding women in the Gaza Strip was done to collect primary data. The findings demonstrate that four variables—product, price, place, and promotion—have an impact on the demarketing of breast milk alternatives for a variety of reasons. Policymakers may use the study’s insights into the factors influencing the demarketing of breast milk alternatives to create successful strategies for promoting breastfeeding and controlling the marketing of these products. The study also emphasizes how important it is for producers to use moral marketing techniques and create products that are more in line with the WHO International Code of Marketing of Breast-milk Substitutes.

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Titel: Analysis of Data Clustering: Factors Influencing the Demarketing of Breast Milk Alternatives
verfasst von: Samer Yaghi
Samir Baidoun
Mohammed Salem
Verlag: Springer Nature Switzerland
Buch: AI and Business, and Innovation Research: Understanding the Potential and Risks of AI for Modern Enterprises
Print ISBN: 978-3-031-42084-9

Electronic ISBN: 978-3-031-42085-6

Copyright-Jahr: 2024
DOI: https://doi.org/10.1007/978-3-031-42085-6_33

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