How Positive and Negative Electronic Word of Mouth (Ewom) Affects Customers’ Intention to Use New Online Channels : A Dual Stage Multi Group-Sem and Ann Analysis

Advances in Web 2.0 technologies have led to the wide adoption of electronic commerce platforms as an innovative shopping method to replace traditional shopping. However, due to pro-technology bias, scholars focus on technology adoption and slightly attention has been paid to the impact of electronic word of mouth (eWOM) on customers’ intention to use new online channels. This study addresses this gap by examining this intention through exploring the effect of eWOM on male and female intentions and identifying the mediation of perceived crowding. We adopt a dual-stage multi-group structural equation modeling and artificial neural network (SEM-ANN) approach. We successfully extend the eWOM concept by integrating negative and positive factors and perceived crowding. The results reveal the causal and non-compensatory relationships between the constructs. The variables supported by the SEM analysis are adopted as the ANN model's input neurons. According to the natural significance obtained from the ANN approach, the intentions of males to accept new online channels are related mainly to perceived crowding, followed by affective factors. In contrast, females are highly influenced by mishandling and aesthetics. The ANN model predicts customers' intentions to use new online channels with an accuracy of 97%. Based on our findings, we discuss theoretical and practical implications for increasing customers' intention towards new online channels amongst consumers