Can machine learning approaches predict green purchase intention? : A study from Indian consumer perspective

This paper explores consumer green consumption practices and considers a set of factors, including cognitive and behavioural level constructs, that influence green consumption. The paper primarily aims to predict the green purchase intention and classify a consumer as a green or non-green consumer. A total of 310 responses were collected and analyzed using machine Learning techniques like Decision Tree, Random Forest, Gradient Boosting, XGBoost, K-Nearest Neighbour, and Support Vector Machine, and the models were validated using different performance metrics. The paper reveals that the main driving factors for a consumer to consider greener options are green self-identification, followed by environmental knowledge, environmental consciousness, and the impact of social media. The current work will allow better product development and the targeting and positioning of green products/services offerings to customers already classified by the system.
CC BY 4.0 DEED© 2024 The AuthorsCorrespondence Address: Y. Liu; Department of Management and Engineering, Linköping University, Linköping, SE-581 83, Sweden; email: yang.liu@liu.se; CODEN: JCROE