The rapid growth of e-commerce has transformed consumer buying behavior significantly by providing more convenience, accessibility, and efficiency but this growth has also brought environmental degradation by increase of carbon emissions from manufacturing, packaging, warehousing, transportation and delivery. As global awareness of sustainability increases, most existing e-commerce platforms are largely focused on profitability, operational efficiency and improving user experience with little to no information provided on the environmental impact of consumer purchases. This means consumers are often unable to make informed decisions about the carbon footprint connected to the products they choose to buy. To tackle this challenge, this study proposes EcoMart, a sustainable e-commerce platform that aims at embedding environmental consciousness into the online shopping process by tracking carbon footprints at the product and order levels. The platform merges traditional e-commerce features such as product browsing, cart management, secure user authentication, and order processing with a hybrid intelligent carbon tracking system. EcoMart uses the Climatiq Carbon API to provide real-time carbon emission estimates related to products and logistics activities at various stages of the product lifecycle. These calculations are based on internationally recognized Greenhouse Gas (GHG) Protocol standards, which allow the platform to offer transparent sustainability information to users throughout the entire purchasing process. The platform has a fallback mechanism using machine learning to make sure that emission estimation is not interrupted, because real- time emission data may not be available in all cases due to limited supplier disclosures, incomplete lifecycle assessment data or API limitations. In particular, an Extreme Gradient Boosting (XGBoost) model is employed to predict carbon emissions based on several product-specific attributes, including product category, material composition, weight, packaging specifications, manufacturing details, and transportation-related factors. The proposed hybrid approach improves the accuracy, scalability, and overall reliability of the carbon footprint estimation in e-commerce environments. EcoMart promotes carbon transparency and has a Green Points Incentive Module which is a gamified reward system that is meant to incentivize environmentally responsible purchasing behavior. Consumers can earn Green Points by selecting products with lower carbon emissions, which they can then use for discounts and other benefits. The proposed platform seeks to connect sustainability knowledge with consumer purchasing behavior through combining sustainability analytics with behavioral motivation strategies to encourage more sustainable consumption practices.
Sustainable E-commerce, Carbon Footprint Estimation, Climatiq API, Green House Gas Protocol, XGBoost, Machine Learning, Green Points, Environmental Sustainability, Intelligent E-commerce Systems, Green Computing.
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