The Role of Voice-Activated Technologies in Shaping Podcast Engagement and Service Satisfaction: A Theoretical and Empirical Synthesis Through HMC Framework

The rapid growth of the global podcast industry, combined with the widespread adoption of voice-activated technologies, is transforming how audiences discover, access, and interact with audio content. Voice assistants embedded in smart devices enable hands-free, conversational access to podcasts, reshaping listening habits and embedding audio consumption within everyday routines. However, while research on podcast engagement and voice assistants has developed independently, limited attention has been given to how voice-activated interfaces influence podcast consumption experiences. Drawing on the Human–Machine Communication (HMC) framework, this study investigates how technological characteristics of voice-enabled platforms—specifically voice interface quality and smart features integration—affect user perceptions and behavioral outcomes. The model proposes that these technology factors influence perceived usefulness, service quality, and interactive experience quality, which subsequently drive user engagement and service satisfaction. Furthermore, technology readiness is examined as a moderating factor shaping how users respond to these technological capabilities. By integrating micro-level user experience outcomes with broader discussions on human-centered AI and digital infrastructure, the study contributes to understanding how AI-driven conversational interfaces can support more inclusive, efficient, and user-oriented digital media ecosystems aligned with Sustainable Development Goal 9 (Industry, Innovation, and Infrastructure).