Predicting online buying behaviour - a comparative study using three classifying methods
by Sanjeev Prashar; T. Sai Vijay; Chandan Parsad
International Journal of Business Innovation and Research (IJBIR), Vol. 15, No. 1, 2018

Abstract: Online retailing with its increasing foothold has made India one of the most anticipated destinations for both local and multinational retailers. The success of these online retailers will depend on their ability to attract more and more consumers to shop online. Therefore, it is pertinent to comprehend and understand consumers' attitude and behaviour towards online shopping, besides predicting online buying potential. This empirical study investigates the accuracy of prediction of different classifiers used in determining online buying. We empirically compared the forecasting ability of neural network (NN), linear discriminant analysis (LDA) and k-nearest neighbour (kNN) in the context of consumers' willingness to shop online. Statistical evidence has been provided that neural network significantly outperforms the other two models in terms of the predicting power. This study shall contribute to online retailers in reducing their vulnerability with respect to market demand and improve their preparedness to handle the market response.

Online publication date: Mon, 11-Dec-2017

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Business Innovation and Research (IJBIR):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com