Application of neural networks technique in predicting impulse buying among shoppers in India

Abstract

Post-economic liberalization, Indian retail industry has been experiencing drastic changes in the consumer buying pattern. Increase in disposable income, easy availability of credit, and growth of shopping malls has increased the impulsive buying behaviour. A vast number of retailers and marketers believe that purchasing decisions are generally made inside the store. To capture the attention of shoppers, retailers invest a huge amount on in-store promotion and store environment endeavouring to enhance shopper experience. Unable to accurately predict the impulsive buying behaviour of their shoppers, retailers get caught in either stockpile or stock out conditions. For years, marketers have been generically forecasting sales for their retail outlets. However, despite various forecasting techniques available, predicting impulsive purchasing has remained under-explored. This paper addresses this gap using neural network model to predict such buying behaviour. With statistical evidence, neural network model has been found to be significantly good in terms of its predicting power. To gain more insights from the model, authors have identified the factors that have significant impact on customers’ impulsive buying. The findings of the study offer a number of implications for retailers and marketers. Future research and managerial implications have also been addressed.