Affiliation:
1. Department of Business Administration, University of Kalyani, India
Abstract
In the context of fastest growing Indian online market, the big players like Amazon.in, Flipkart.com, Snapdeal.com, etc. are in a competitive journey to expand their market share. This paper is an attempt in modelling customer feedback for the said e-market players. The paper uses feed forward neural networks with maximum two hidden layers and back propagation kind of supervised learning algorithm. The paper found satisfactory level of success and concludes usefulness of customer feedback for both customers (for purchase decision) and marketers (for product development) points of view. It is a footstep and opens a new research challenge for the post-COVID era of business.
Cited by
4 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. K-Means Clustering for Smart Cities: An Empirical Study in Indian Context;International Journal of Soft Computing and Engineering;2024-07-30
2. The Dramatic Fail and Fall of Huge Startup Snapdeal: A Case Study;International Journal of Case Studies in Business, IT, and Education;2023-11-29
3. AI-Based Sales Forecasting Model for Digital Marketing;International Journal of E-Business Research;2023-02-10
4. Privacy Preserved and Decentralized Smartphone Recommendation System;IEEE Transactions on Consumer Electronics;2023