Machine Learning Applications in Market Basket Analysis: A Case Study on Electric Vehicle Sales in India

This study explores the potential of Market Basket Analysis (MBA) to enhance electric vehicle (EV) recommendations in India. By analyzing transactional data and identifying common item sets and association rules, MBA can provide valuable insights into customer preferences and purchasing behavior. This information can be utilized to develop personalized recommendation systems that effectively guide customers toward EV solutions tailored to their specific needs and preferences. These include discussions on key drivers of EV purchases in India, steps for implementing MBA, and challenges/concerns about the application of MBA. Specific factors in buying decisions can be traced through the analysis of unique characteristics in the Indian EV market. Finally, potential benefits are presented with the implementation of an MBA-driven recommendation system to both the manufacturer and the consumers of electric vehicles in India. The study will delve deep into the application of MBA in the Indian EV market and contribute toward more effective and customized recommendation systems for the industry at large.

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Publication Details

Published
2025-03-06
DOI
https://doi.org/10.1109/iatmsi64286.2025.10984629
Primary Topic
Energy, Environment, and Transportation Policies
Type
article
Field-Weighted Citation Impact
0.00
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Machine Learning Applications in Market Basket Analysis: A Case Study on Electric Vehicle Sales in India

Gaurav Sethi, Ashish Singh Chauhan, Rachna Rathore, Ashok Kumar Mishra et al.
Energy, Environment, and Transportation Policies
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Machine Learning Applications in Market Basket Analysis: A Case Study on Electric Vehicle Sales in India

Gaurav Sethi, Ashish Singh Chauhan, Rachna Rathore, Ashok Kumar Mishra, Kailash Aseri, J. Balaji Praveen
article en

Abstract

This study explores the potential of Market Basket Analysis (MBA) to enhance electric vehicle (EV) recommendations in India. By analyzing transactional data and identifying common item sets and association rules, MBA can provide valuable insights into customer preferences and purchasing behavior. This information can be utilized to develop personalized recommendation systems that effectively guide customers toward EV solutions tailored to their specific needs and preferences. These include discussions on key drivers of EV purchases in India, steps for implementing MBA, and challenges/concerns about the application of MBA. Specific factors in buying decisions can be traced through the analysis of unique characteristics in the Indian EV market. Finally, potential benefits are presented with the implementation of an MBA-driven recommendation system to both the manufacturer and the consumers of electric vehicles in India. The study will delve deep into the application of MBA in the Indian EV market and contribute toward more effective and customized recommendation systems for the industry at large.

Chandigarh University (IN), Jiwaji University (IN), Lovely Professional University (IN), Uttaranchal University (IN), Dhanalakshmi Srinivasan Group of Institutions (IN)
Openalex Percentile: Top 94%
Energy, Environment, and Transportation Policies
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