Analyzing Customer Decision-Making in Indian E-Commerce: A Study Using Decision Tree and K-Nearest Neighbor
Publish Year: 1402
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
ICISE09_023
تاریخ نمایه سازی: 15 مهر 1402
Abstract:
The advent of technology has brought about a major shift in the way businesses operate. Electronic Commerce has revolutionized the way consumers purchase goods and services. With the increasing popularity of online shopping in India, it is essential to understand the factors influencing customer decision-making processes. This paper aims to study e-commerce and examine the decision-making processes of customers in India. The study was based on data collected through a questionnaire designed under the title "E-Tailing Customer Survey in India", which was published by Kaggle. The survey aims to evaluate the various factors influencing e-commerce in India. Customers responded to multiple-choice questions about various factors related to e-commerce and evaluated different criteria. To analyze the collected data, data visualization techniques using Tableau and Google Data Studio were employed. Additionally, machine learning techniques, including Decision Trees and K-Nearest Neighbors, were applied. The findings of this research will help e-commerce businesses in India better understand the decision-making processes of their customers. The study's results can also help businesses optimize their marketing strategies and improve their services based on the needs and preferences of their customers. Overall, this paper will contribute to the existing body of knowledge on e-commerce and customer decision-making processes in India.
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Authors
Kiana Amani
Department of Industrial Engineering, Faculty of Engineering, Alzahra University, Tehran, Iran;
Reza Samizadeh
Department of Industrial Engineering, Faculty of Engineering, Alzahra University, Tehran, Iran;
Mehdi Seifbarghy
Department of Industrial Engineering, Faculty of Engineering, Alzahra University, Tehran, Iran;