Understand Consumer’s Product Decisions when Shopping by Voice

Using deep learning and natural language processing technologies, many e-merchants nowadays start offering artificially intelligent virtual assistant on their website or through mobile applications to assist consumer’s online shopping (e.g., Amazon Alexa, Domino’s DRU assist). Compared with traditional online shopping that is navigated by point and click, shopping with virtual assistant resembles two-way communication process between humans, allowing consumers to place an order by typing or speaking. In this research, I hypothesize that interaction modalities between consumer and virtual assistant will influence the perceived socialness of website, and consequently affect consumer’s acceptance of recommendations. A real online shopping website is developed to test the hypotheses.

Many thanks to Zhen’s dissertation committee: • Committee Chair: Yanliu Huang – Associate Professor – Drexel University • Committee Member: Chen Wang - Assistant Professor – Drexel University • Committee Member Bert Rosenbloom - Professor- Drexel University • Committee Member: Trina Andras - Professor – Drexel University • Committee Member: Barbara Kahn - Professor – University of Pennsylvania