Evolution of Interactivity from B2C to C2C: Exploring Flow Theory and WOM—An Abstract

Abstract

While overall e-commerce sales in the USA are continuing to grow, the giant e-commerce site, amazon.com, is outperforming all of the others in the e-commerce industry. So the question arises: What makes Amazon more successful than the others? The answer to this question is critical for other e-tailers who would like to benchmark Amazon. Among a variety of reasons, Amazon’s highly interactive site is one of its strengths. Amazon aims for a higher level of interactivity with customers via live chatting, e-mail, etc., and provides proactive personalization such as a recommendation system (Edelman and Singer 2015) and easy access to customer reviews on the site. Accordingly, we explored the relevant influences of the B2C versus C2C interactivity feature quality on loyalty intention mediated by flow and the technology acceptance model. In addition, the moderating effect of proactive engagement in word of mouth (WOM) was examined because the relative importance of others’ opinions could be different for those who value creating and sharing their own opinions with others. Participants in the current study were recruited using a US online consumer panel and were included if they had shopped at amazon.com within 12 months prior to the start of the study. After confirming the latent measurement model fit of the data, we tested the hypotheses using AMOS 20.0. First, several indices evaluating model fit appropriateness were analyzed. Based on good model fit, the hypotheses were tested and they yielded results supporting all the hypotheses except one: expecting the influence of perceived ease of use on repurchase intention online. A subsequent test was conducted to investigate the moderating effect of proactive engagement in WOM. Interestingly, once the moderating effect was included in the model, the effect of interactivity among consumers on flow was no longer significant, which could mean that consumers who were actively producing their own WOM were not much influenced by other consumers’ input. This might be because consumers who tend to be opinion leaders or WOM creators trust their own experiences and judgements more than someone else’s. Another interesting finding is that those who were less involved in WOM creation relied more on one-way interactivity from sellers than those who were more actively involved in WOM creation. This could be because consumers who do not create WOM tend to rely more on information given by sellers rather than on actively searching for more information through communicating with others. Finally, two-way interactivity between seller and consumer had both a significant and a negative effect on flow in the main model, but this effect was not significant in the moderating model. Considering that the quality of the interactivity feature and the frequency of using the feature were highly correlated, those who contacted sellers more often and perceived a higher quality of the features were less likely to experience flow. This is understandable because consumers usually contact sellers when they encounter problems, which could interrupt their flow experience.