Predicting actual spending in online group buying - An artificial neural network approach

Abstract

Abstract With the widespread of the Internet and Web 2.0 applications, the way products are being sold has been transformed from the traditional individual purchases to group buying. Popularly known as online group buying or OGB, this new way of selling products has enormous potential for online businesses. Even though various studies have been conducted to examine consumers’ intention to repurchase, revisit or continuance intention however such intentions may not necessarily lead to actual spending. The aim of the study is to identify the factors that drive consumers’ actual spending in OGB. Unlike previous studies which used linear regression models, through the use of the artificial neural network, we successfully identified the linear and nonlinear effects of trust, price consciousness, ease of use, usefulness, gender and Internet time spent on consumers’ actual spending in OGB. The research model predicts with an accuracy of 87.14%. Theoretical and practical implications are discussed.