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Analyzing the Relationship Between Product Buying Behavior and Individual Salary

A Classification and Regression Analysis

Bibliographic Data

ID22197300
AuthorsRajendra Singh (0000-0002-3301-0083, Department of Commerce), Raghvendra Singh (0000-0003-2389-584X), Mousami Singh (0000-0002-0845-7887, Department of Commerce)
Year2024
Volume5
Issue6
Publication date2024-06-30
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueShodhKosh: Journal of Visual and Performing Arts (JOURNAL)
Journal identifiersISSN: 2582-7472 • E-ISSN: 2582-7472
PublisherGranthaalayah Publications and Printers (PUBLISHER • IN)
DOI10.29121/shodhkosh.v5.i6.2024.2110
OpenAlexW4402869998
LanguageEN
References cited9

This paper investigates the correlation between individual salary levels and product buying behavior through a comprehensive analysis employing both classification and regression techniques. The study aims to discern patterns and predict future buying behavior based on the income of consumers. In the classification analysis, various demographic and socio-economic factors are utilized to classify individuals into different income brackets. This step enables the segmentation of the population based on their salary levels, facilitating a deeper understanding of the relationship between income and buying preferences. Following the classification analysis, regression techniques are employed to quantify the impact of salary on specific buying behaviors. By analyzing historical data on product purchases across different income groups, regression models are developed to predict the purchasing patterns associated with varying salary levels. This predictive capability enables businesses to tailor their marketing strategies and product offerings to different income segments more effectively

Econometrics · Economics · Linear regression · Regression · Regression analysis · Salary · Statistics · Consumer Retail Behavior Studies · Customer Service Quality and Loyalty · Mathematics · Psychology · Technology Adoption and User Behaviour

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Citation velocityhistorical
Highly citedNo

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