Dissertation, Otto-Friedrich-Universität Bamberg, 2024

Voice technologies, mainly in the form of voice assistants, accompany consumers in their daily lives (Dellaert et al. 2020). Voice assistants are implemented, for instance, in smartphones or in smart speakers, such as Amazon Alexa (Rzepka, Berger, and Hess 2020). These evolving voice-based human–computer interactions offer companies and brands a new marketing form: voice marketing. The topic of voice marketing stimulates great interest among academic researchers and marketing practitioners. However, voice-marketing research is still in its infancy and existing findings are scattered. Therefore, this dissertation presents three studies to illuminate central voice-marketing issues.
The first study was focused on structuring the evolving research field of voice marketing and developing a research agenda. To do so, a quantitative bibliometric analysis and a qualitative semi-systematic literature were conducted. The second study was concerned with uncovering significant differences between text-based and speech-based conversational agents. The study revealed that marketing communications through text- and speech-based conversational agents arouse positive effects, e.g. on perceived brand warmth and competence. However, the agents differ significantly in their core effects. In the third study, a specific voice-marketing communication tool was investigated: voice-assistant applications developed by brands or companies. The study resulted in the development of the VAMEM (the value-based adoption and marketing effects model) as a measurement instrument to capture the marketing performance of voice-assistant applications moving forward.