Understanding Consumer Decision-Making in Online Shopping
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This study investigates the key contextual and behavioral factors that influence purchase intentions in the swimwear category on a major online retail platform, referred to as Company X. Using the Stimulus-Organism-Response (S-O-R) framework, we analyze session-level data from 2021 to 2022, incorporating variables such as weather conditions, device type, customer demographics, and purchasing time. The analysis employs a logistic regression model to evaluate how these factors affect the likelihood of purchase activity. The results reveal that customer loyalty, gender, device type, weather (cold and hot days), and purchase timing significantly influence consumer behavior, while factors like competition, sunny days, and long holidays show no significant effect. The model explains approximately 27% of the variance in purchase activity. The findings offer actionable insights for e-commerce strategies, such as targeted seasonal promotions and product recommendations that are responsive to contextual conditions, thereby supporting data-driven decision-making and improved inventory management.
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This work is licensed under a Creative Commons Attribution 4.0 International License.
This work is licensed under a Creative Commons Attribution 4.0 International.
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