An empirical study on user buying behaviour in fashion industry using logistic regression. (17th December 2021)

• Record Type: Journal Article
• Authors: Chauhan, Shaifali; Banerjee, Richa; Mittal, Mohit; Bhakar, Sher Singh
• Is Part Of: International journal of engineering systems modelling and simulation. Volume 12:Number 4(2021)
• Page Start: 252
• Page End: 263
• Publication Date: 2021-12-17
• Subjects: buying behaviour -- logistic regression -- support vector machine -- fashion apparels; Engineering systems -- Computer simulation -- Periodicals; Engineering systems -- Mathematical models -- Periodicals; 620.0042
• Languages: English
• ISSNs: 1755-9758

Abstract

The potential growth in technology is very high from past two decades. Due to this, every field of life is connected to internet. Nowadays, millions of people use internet and do shopping online. The fashion industry has opened new gates for online users by providing various offers. In this paper, a model is proposed for analysing impulse buying (IB) towards apparels based on consumers' shopping behaviour. The data of 569 responses is collected and evaluated by using partial least square-structural equation modelling framework. Further, for analysing and identification of exact parameters that is highly important which affect user buying behaviour has used statistical approaches such as logistic regression. Based on results, hedonic and positive emotions (PE) have a significant impact on impulse buying, whereas involvement and sales promotion have an insignificant relationship.