DESIGN AND ANALYSIS OF FRAMEWORK TO PREDICT ONLINE SHOPPING BEHAVIOUR OF CONSUMERS IN CUDDALORE DISTRICT

Abstract

Online shopping has significantly reshaped consumer behaviour, offering enhanced convenience and product diversity. However, understanding the specific factors driving online shopping behaviour remains challenging, particularly in semi-urban regions with unique socio-economic profiles. This study addresses this gap by proposing and validating a novel framework, CUDDLE-SHOP (Cuddalore District’s E-Commerce Shopping Habit and Opportunity Predictor), to predict online shopping behaviour in Cuddalore District. The framework integrates demographic, technological, behavioural, psychographic, social, and economic factors to provide insights into consumer preferences and purchasing patterns in this distinct region. The study employs various analytical techniques, including surveys, statistical analysis, and machine learning models, to validate the framework. Key findings reveal that younger consumers with higher incomes are more inclined towards online shopping, while lower digital literacy among older individuals suggests a need for improved user interfaces and educational initiatives. Behavioural trends indicate a preference for convenience and competitive pricing, while social influences and economic conditions play significant roles in shaping shopping behaviour. The CUDDLE-SHOP framework offers actionable insights for businesses to tailor their e-commerce strategies, optimize online platforms, and enhance customer engagement specific to Cuddalore. The study emphasizes the importance of addressing local consumer needs through targeted marketing and digital literacy programs.